{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### This notebook implements the low pass filter logic for smoothing of the discrete signals."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Date created = 26 March 2019\n",
    "\n",
    "Date Finished = 26 March 2019\n",
    "\n",
    "Conclusion = Here, Outlier Detection and Imputation was done by the use of **Butterworth Low Pass Filter** and **RC Filter**. Both these approaches failed to generate good results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing the libraries\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import os\n",
    "import scipy\n",
    "import scipy.signal as sig\n",
    "from scipy.signal import butter, lfilter, freqz\n",
    "from scipy.signal import savgol_filter\n",
    "import random\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [],
   "source": [
    "# setting up visualization and pandas parameters\n",
    "\n",
    "os.chdir(\"/home/CWSHPMU2316/Desktop/EVRangePrediction/data/raw\")\n",
    "pd.set_option(\"display.max_columns\", 200)\n",
    "plt.rcParams[\"figure.figsize\"] = (10, 10)\n",
    "sns.set_style(\"darkgrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "# selecting a file at random\n",
    "\n",
    "### vehicleList ###\n",
    "# list of all the vehicles used in analysis\n",
    "# this list will help in randomly selecting the files to be used in analysis\n",
    "\n",
    "vehicleList = [352891066262326, 352891066262722, 352891066262995, 352891066263282, 352891066264694, 352891066265451, \\\n",
    "               358272088698868, 358272088699007, 358272088699072, 358272088701548, 358272088709954, 358272088712370, \\\n",
    "               358272088715043, 358272088715191, 358272088716215, 358272088718575, 358272088730844]\n",
    "\n",
    "\n",
    "\n",
    "def randomDate(start, end, format, prop):\n",
    "    \"\"\"\n",
    "    generates a date within the window of start and end\n",
    "    \"\"\"\n",
    "    stime = time.mktime(time.strptime(start, format))\n",
    "    etime = time.mktime(time.strptime(end, format))\n",
    "    ptime = stime + prop * (etime - stime)\n",
    "    return time.strftime(format, time.localtime(ptime))\n",
    "\n",
    "\n",
    "def randomDateGenerator(start, end, prop):\n",
    "    \"\"\"\n",
    "    calls the function randomDate() and defines the format of the date\n",
    "    \"\"\"\n",
    "    return randomDate(start, end, '%Y-%m-%d', prop)\n",
    "\n",
    "def csv():\n",
    "    \"\"\"\n",
    "    returns a csv file name.\n",
    "    \"\"\"\n",
    "    return str(random.choice(vehicleList))+\"_\"+randomDateGenerator(\"2018-11-01\", \"2019-01-27\", random.random()) + \"_cb.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "file = 358272088716215_2018-12-01_cb.csv\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mo</th>\n",
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       "      <th>EVIGS</th>\n",
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       "      <th>EVVSP</th>\n",
       "      <th>EVDRG</th>\n",
       "      <th>EVGPO</th>\n",
       "      <th>EVBRP</th>\n",
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       "      <th>EVBAP_Min</th>\n",
       "      <th>EVCCS</th>\n",
       "      <th>EVCM1</th>\n",
       "      <th>EVCTM</th>\n",
       "      <th>EVCCU</th>\n",
       "      <th>EVCSD</th>\n",
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       "      <th>EVPSC_Latest</th>\n",
       "      <th>EVPSC_Max</th>\n",
       "      <th>EVPSC_Min</th>\n",
       "      <th>EVVOU</th>\n",
       "      <th>EVCOU</th>\n",
       "      <th>EVCPV</th>\n",
       "      <th>EVVCD</th>\n",
       "      <th>EVCCD</th>\n",
       "      <th>EVCSC</th>\n",
       "      <th>EVEST</th>\n",
       "      <th>EVCHS</th>\n",
       "      <th>EVR10</th>\n",
       "      <th>EVRMN</th>\n",
       "      <th>EVHVS</th>\n",
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       "      <th>EVMCV_MIN</th>\n",
       "      <th>EVSMA_MAX</th>\n",
       "      <th>EVSMA_MIN</th>\n",
       "      <th>EVSMI_MAX</th>\n",
       "      <th>EVSMI_MIN</th>\n",
       "      <th>EVSOH</th>\n",
       "      <th>EVBMA_Latest</th>\n",
       "      <th>EVBMA_Max</th>\n",
       "      <th>EVBMA_Min</th>\n",
       "      <th>EVBMI_Latest</th>\n",
       "      <th>EVBMI_Max</th>\n",
       "      <th>EVBMI_Min</th>\n",
       "      <th>EVBOA_AVG</th>\n",
       "      <th>EVBOA_MAX</th>\n",
       "      <th>EVBOA_MIN</th>\n",
       "      <th>EVBOV_AVG</th>\n",
       "      <th>EVBOV_MAX</th>\n",
       "      <th>EVBOV_MIN</th>\n",
       "      <th>EVIRP</th>\n",
       "      <th>EVIRN</th>\n",
       "      <th>EVSOMA</th>\n",
       "      <th>EVSOMI</th>\n",
       "      <th>EVIGM_Latest</th>\n",
       "      <th>EVIGM_Max</th>\n",
       "      <th>EVIGM_Min</th>\n",
       "      <th>EVCOM_Latest</th>\n",
       "      <th>EVCOM_Max</th>\n",
       "      <th>EVCOM_Min</th>\n",
       "      <th>EVICO_Latest</th>\n",
       "      <th>EVICO_Max</th>\n",
       "      <th>EVICO_Min</th>\n",
       "      <th>EVIRT_Latest</th>\n",
       "      <th>EVIRT_Max</th>\n",
       "      <th>EVIRT_Min</th>\n",
       "      <th>EVIDC</th>\n",
       "      <th>EVMGT</th>\n",
       "      <th>EVMGS</th>\n",
       "      <th>EVMGF</th>\n",
       "      <th>EVMGR</th>\n",
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       "      <th>EVICM</th>\n",
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       "      <th>EVCPF_Min</th>\n",
       "      <th>EVCI1_Latest</th>\n",
       "      <th>EVCI1_Max</th>\n",
       "      <th>EVCI1_Min</th>\n",
       "      <th>EVCI2_Latest</th>\n",
       "      <th>EVCI2_Max</th>\n",
       "      <th>EVCI2_Min</th>\n",
       "      <th>EVCBD_Latest</th>\n",
       "      <th>EVCBD_Max</th>\n",
       "      <th>EVCBD_Min</th>\n",
       "      <th>EVCRP</th>\n",
       "      <th>EVACV_AVG</th>\n",
       "      <th>EVACV_Max</th>\n",
       "      <th>EVACV_Min</th>\n",
       "      <th>EVCDO_AVG</th>\n",
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       "      <th>Unnamed: 164</th>\n",
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       "      <td>-50</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>106</td>\n",
       "      <td>202</td>\n",
       "      <td>15</td>\n",
       "      <td>-50</td>\n",
       "      <td>-16</td>\n",
       "      <td>14</td>\n",
       "      <td>88</td>\n",
       "      <td>212</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>260</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.225</td>\n",
       "      <td>52.9</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2572</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>-820</td>\n",
       "      <td>654</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547605702600</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>87.78603</td>\n",
       "      <td>1036056339</td>\n",
       "      <td>5</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>246</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>60.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.88</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.1</td>\n",
       "      <td>78.1</td>\n",
       "      <td>100</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-505.0</td>\n",
       "      <td>-357.0</td>\n",
       "      <td>257.75</td>\n",
       "      <td>174.0</td>\n",
       "      <td>16180.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1790</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "      <td>-50</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>106</td>\n",
       "      <td>202</td>\n",
       "      <td>15</td>\n",
       "      <td>-50</td>\n",
       "      <td>-16</td>\n",
       "      <td>14</td>\n",
       "      <td>88</td>\n",
       "      <td>212</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>260</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.225</td>\n",
       "      <td>52.9</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2572</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>-820</td>\n",
       "      <td>654</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547605702700</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>87.78603</td>\n",
       "      <td>1036056339</td>\n",
       "      <td>5</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>246</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>60.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.88</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.1</td>\n",
       "      <td>78.1</td>\n",
       "      <td>100</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-505.0</td>\n",
       "      <td>-357.0</td>\n",
       "      <td>257.75</td>\n",
       "      <td>174.0</td>\n",
       "      <td>16180.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1790</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "      <td>-50</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>106</td>\n",
       "      <td>202</td>\n",
       "      <td>15</td>\n",
       "      <td>-50</td>\n",
       "      <td>-16</td>\n",
       "      <td>14</td>\n",
       "      <td>88</td>\n",
       "      <td>212</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>260</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.225</td>\n",
       "      <td>52.9</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2572</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>-820</td>\n",
       "      <td>654</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547605702800</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>87.78603</td>\n",
       "      <td>1036056339</td>\n",
       "      <td>5</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>246</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>60.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.88</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.1</td>\n",
       "      <td>78.1</td>\n",
       "      <td>100</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-505.0</td>\n",
       "      <td>-357.0</td>\n",
       "      <td>257.75</td>\n",
       "      <td>174.0</td>\n",
       "      <td>16180.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1790</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "      <td>-50</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>106</td>\n",
       "      <td>202</td>\n",
       "      <td>15</td>\n",
       "      <td>-50</td>\n",
       "      <td>-16</td>\n",
       "      <td>14</td>\n",
       "      <td>88</td>\n",
       "      <td>212</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>260</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.225</td>\n",
       "      <td>52.9</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2572</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>-820</td>\n",
       "      <td>654</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       mo                tp  dr         ln         lt   hd  \\\n",
       "0  DEFREG:358272088715191  Trip not started NaN  76.951081  28.390039  1.0   \n",
       "1  DEFREG:358272088715191  Trip not started NaN  76.951081  28.390039  1.0   \n",
       "2  DEFREG:358272088715191  Trip not started NaN  76.951081  28.390039  1.0   \n",
       "3  DEFREG:358272088715191  Trip not started NaN  76.951081  28.390039  1.0   \n",
       "4  DEFREG:358272088715191  Trip not started NaN  76.951081  28.390039  1.0   \n",
       "\n",
       "   sp             tm         mn         mt        mh          ml  mr  \\\n",
       "0 NaN  1547605702400  76.951081  28.390039  87.78603  1036056339   5   \n",
       "1 NaN  1547605702500  76.951081  28.390039  87.78603  1036056339   5   \n",
       "2 NaN  1547605702600  76.951081  28.390039  87.78603  1036056339   5   \n",
       "3 NaN  1547605702700  76.951081  28.390039  87.78603  1036056339   5   \n",
       "4 NaN  1547605702800  76.951081  28.390039  87.78603  1036056339   5   \n",
       "\n",
       "   SpeedLimit  hdop  numsat             IMEI           trip_id EVTmg  \\\n",
       "0        30.0   1.8       7  358272088715191  Trip not started     P   \n",
       "1        30.0   1.8       7  358272088715191  Trip not started     P   \n",
       "2        30.0   1.8       7  358272088715191  Trip not started     P   \n",
       "3        30.0   1.8       7  358272088715191  Trip not started     P   \n",
       "4        30.0   1.8       7  358272088715191  Trip not started     P   \n",
       "\n",
       "        EVVer  EVCfg  EVIGS  EVIGC  EVVSP  EVDRG  EVGPO  EVBRP  EVCFN  EVICR  \\\n",
       "0  M1_POCEV.0    NaN      1    246    0.0     87     10      0      0      1   \n",
       "1  M1_POCEV.0    NaN      1    246    0.0     87     10      0      0      1   \n",
       "2  M1_POCEV.0    NaN      1    246    0.0     87     10      0      0      1   \n",
       "3  M1_POCEV.0    NaN      1    246    0.0     87     10      0      0      1   \n",
       "4  M1_POCEV.0    NaN      1    246    0.0     87     10      0      0      1   \n",
       "\n",
       "   EVTRQ  EVCST  EVDDC  EVBCA  EVBBV  EVDR1  EVDR2  EVRGT  EVACP  \\\n",
       "0    0.0      1   13.9      0   60.5      0      0      0    0.0   \n",
       "1    0.0      1   13.9      0   60.5      0      0      0    0.0   \n",
       "2    0.0      1   13.9      0   60.5      0      0      0    0.0   \n",
       "3    0.0      1   13.9      0   60.5      0      0      0    0.0   \n",
       "4    0.0      1   13.9      0   60.5      0      0      0    0.0   \n",
       "\n",
       "   EVBAP_Latest  EVBAP_Max  EVBAP_Min  EVCCS  EVCM1  EVCTM  EVCCU  EVCSD  \\\n",
       "0             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "1             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "2             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "3             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "4             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "\n",
       "   EVVCE  EVPSC_Latest  EVPSC_Max  EVPSC_Min  EVVOU  EVCOU  EVCPV  EVVCD  \\\n",
       "0    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "1    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "2    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "3    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "4    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "\n",
       "   EVCCD  EVCSC  EVEST  EVCHS  EVR10  EVRMN  EVHVS  EVV12  EVPWA_MAX  \\\n",
       "0    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "1    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "2    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "3    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "4    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "\n",
       "   EVPWA_MIN  EVMCV_MAX  EVMCV_MIN  EVSMA_MAX  EVSMA_MIN  EVSMI_MAX  \\\n",
       "0          0       3.89       3.88       78.4       78.4       78.1   \n",
       "1          0       3.89       3.88       78.4       78.4       78.1   \n",
       "2          0       3.89       3.88       78.4       78.4       78.1   \n",
       "3          0       3.89       3.88       78.4       78.4       78.1   \n",
       "4          0       3.89       3.88       78.4       78.4       78.1   \n",
       "\n",
       "   EVSMI_MIN  EVSOH  EVBMA_Latest  EVBMA_Max  EVBMA_Min  EVBMI_Latest  \\\n",
       "0       78.1    100          15.5       15.5       15.5          15.0   \n",
       "1       78.1    100          15.5       15.5       15.5          15.0   \n",
       "2       78.1    100          15.5       15.5       15.5          15.0   \n",
       "3       78.1    100          15.5       15.5       15.5          15.0   \n",
       "4       78.1    100          15.5       15.5       15.5          15.0   \n",
       "\n",
       "   EVBMI_Max  EVBMI_Min  EVBOA_AVG  EVBOA_MAX  EVBOA_MIN  EVBOV_AVG  \\\n",
       "0       15.0       15.0        0.5     -505.0     -357.0     257.75   \n",
       "1       15.0       15.0        0.5     -505.0     -357.0     257.75   \n",
       "2       15.0       15.0        0.5     -505.0     -357.0     257.75   \n",
       "3       15.0       15.0        0.5     -505.0     -357.0     257.75   \n",
       "4       15.0       15.0        0.5     -505.0     -357.0     257.75   \n",
       "\n",
       "   EVBOV_MAX  EVBOV_MIN  EVIRP  EVIRN  EVSOMA  EVSOMI  EVIGM_Latest  \\\n",
       "0      174.0    16180.0   1790   1790     100     100            14   \n",
       "1      174.0    16180.0   1790   1790     100     100            14   \n",
       "2      174.0    16180.0   1790   1790     100     100            14   \n",
       "3      174.0    16180.0   1790   1790     100     100            14   \n",
       "4      174.0    16180.0   1790   1790     100     100            14   \n",
       "\n",
       "   EVIGM_Max  EVIGM_Min  EVCOM_Latest  EVCOM_Max  EVCOM_Min  EVICO_Latest  \\\n",
       "0        -50          2            14        106        202            15   \n",
       "1        -50          2            14        106        202            15   \n",
       "2        -50          2            14        106        202            15   \n",
       "3        -50          2            14        106        202            15   \n",
       "4        -50          2            14        106        202            15   \n",
       "\n",
       "   EVICO_Max  EVICO_Min  EVIRT_Latest  EVIRT_Max  EVIRT_Min  EVIDC  EVMGT  \\\n",
       "0        -50        -16            14         88        212    0.0   -0.1   \n",
       "1        -50        -16            14         88        212    0.0   -0.1   \n",
       "2        -50        -16            14         88        212    0.0   -0.1   \n",
       "3        -50        -16            14         88        212    0.0   -0.1   \n",
       "4        -50        -16            14         88        212    0.0   -0.1   \n",
       "\n",
       "   EVMGS  EVMGF  EVMGR  EVIND  EVICM  EVCPW  EVCPF_Latest  EVCPF_Max  \\\n",
       "0      0    0.0    0.0    260      3    NaN           NaN        NaN   \n",
       "1      0    0.0    0.0    260      3    NaN           NaN        NaN   \n",
       "2      0    0.0    0.0    260      3    NaN           NaN        NaN   \n",
       "3      0    0.0    0.0    260      3    NaN           NaN        NaN   \n",
       "4      0    0.0    0.0    260      3    NaN           NaN        NaN   \n",
       "\n",
       "   EVCPF_Min  EVCI1_Latest  EVCI1_Max  EVCI1_Min  EVCI2_Latest  EVCI2_Max  \\\n",
       "0        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "1        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "2        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "3        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "4        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "\n",
       "   EVCI2_Min  EVCBD_Latest  EVCBD_Max  EVCBD_Min  EVCRP  EVACV_AVG  EVACV_Max  \\\n",
       "0        NaN           NaN        NaN        NaN      1        NaN        NaN   \n",
       "1        NaN           NaN        NaN        NaN      1        NaN        NaN   \n",
       "2        NaN           NaN        NaN        NaN      1        NaN        NaN   \n",
       "3        NaN           NaN        NaN        NaN      1        NaN        NaN   \n",
       "4        NaN           NaN        NaN        NaN      1        NaN        NaN   \n",
       "\n",
       "   EVACV_Min  EVCDO_AVG  EVCDO_Max  EVCDO_Min  EVCCO_AVG  EVCCO_Max  \\\n",
       "0        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "1        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "2        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "3        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "4        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "\n",
       "   EVCCO_Min  EVSDT  EVCHC  EVCHT_AVG  EVCHT_Max  EVCHT_Min  EVCHE  EVDI1  \\\n",
       "0        NaN    NaN    NaN        NaN        NaN        NaN    NaN     15   \n",
       "1        NaN    NaN    NaN        NaN        NaN        NaN    NaN     15   \n",
       "2        NaN    NaN    NaN        NaN        NaN        NaN    NaN     15   \n",
       "3        NaN    NaN    NaN        NaN        NaN        NaN    NaN     15   \n",
       "4        NaN    NaN    NaN        NaN        NaN        NaN    NaN     15   \n",
       "\n",
       "   EVDI2  EVDIT  EVOII  EVDOA  EVDOV  EVDSE  EVACS   EVPSS  EVMSC  EVRER  \\\n",
       "0     14     14      0     27   13.9      0    0.0  46.225   52.9      0   \n",
       "1     14     14      0     27   13.9      0    0.0  46.225   52.9      0   \n",
       "2     14     14      0     27   13.9      0    0.0  46.225   52.9      0   \n",
       "3     14     14      0     27   13.9      0    0.0  46.225   52.9      0   \n",
       "4     14     14      0     27   13.9      0    0.0  46.225   52.9      0   \n",
       "\n",
       "   EVDRV  EVMTR  EVODO  EVOAS  EVHTR  EVACE  EVTRE  EVCLC  EVBFN  EVIST  \\\n",
       "0 -65532      0   2572   13.0      0   13.7   50.0     55      0      0   \n",
       "1 -65532      0   2572   13.0      0   13.7   50.0     55      0      0   \n",
       "2 -65532      0   2572   13.0      0   13.7   50.0     55      0      0   \n",
       "3 -65532      0   2572   13.0      0   13.7   50.0     55      0      0   \n",
       "4 -65532      0   2572   13.0      0   13.7   50.0     55      0      0   \n",
       "\n",
       "   EVHTP_AVG  EVHTP_Max  EVHTP_Min  EVVBT  EVGSM  EVACO_X  EVACO_Y  EVACO_Z  \\\n",
       "0          0          0          0    137      0     -820      654       23   \n",
       "1          0          0          0    137      0     -820      654       23   \n",
       "2          0          0          0    137      0     -820      654       23   \n",
       "3          0          0          0    137      0     -820      654       23   \n",
       "4          0          0          0    137      0     -820      654       23   \n",
       "\n",
       "   Unnamed: 164  \n",
       "0           NaN  \n",
       "1           NaN  \n",
       "2           NaN  \n",
       "3           NaN  \n",
       "4           NaN  "
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filename = csv() # getting the file by above used logic\n",
    "print(\"file = {}\".format(filename))\n",
    "data = pd.read_csv(\"358272088715191_2019-01-16_cb.csv\")\n",
    "\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "# finding out the index across the data, wherever new trip starts\n",
    "# Logic used - whenever the value of EVIGC changes, new trip starts.\n",
    "\n",
    "new_trip = []\n",
    "for i in range(1, len(data)):\n",
    "    if data.EVIGC[i] - data.EVIGC[i-1] >= 1:\n",
    "        new_trip.append(data.index[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[21000, 63600]"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# printing the new trip indices\n",
    "new_trip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mo</th>\n",
       "      <th>tp</th>\n",
       "      <th>dr</th>\n",
       "      <th>ln</th>\n",
       "      <th>lt</th>\n",
       "      <th>hd</th>\n",
       "      <th>sp</th>\n",
       "      <th>tm</th>\n",
       "      <th>mn</th>\n",
       "      <th>mt</th>\n",
       "      <th>mh</th>\n",
       "      <th>ml</th>\n",
       "      <th>mr</th>\n",
       "      <th>SpeedLimit</th>\n",
       "      <th>hdop</th>\n",
       "      <th>numsat</th>\n",
       "      <th>IMEI</th>\n",
       "      <th>trip_id</th>\n",
       "      <th>EVTmg</th>\n",
       "      <th>EVVer</th>\n",
       "      <th>EVCfg</th>\n",
       "      <th>EVIGS</th>\n",
       "      <th>EVIGC</th>\n",
       "      <th>EVVSP</th>\n",
       "      <th>EVDRG</th>\n",
       "      <th>EVGPO</th>\n",
       "      <th>EVBRP</th>\n",
       "      <th>EVCFN</th>\n",
       "      <th>EVICR</th>\n",
       "      <th>EVTRQ</th>\n",
       "      <th>EVCST</th>\n",
       "      <th>EVDDC</th>\n",
       "      <th>EVBCA</th>\n",
       "      <th>EVBBV</th>\n",
       "      <th>EVDR1</th>\n",
       "      <th>EVDR2</th>\n",
       "      <th>EVRGT</th>\n",
       "      <th>EVACP</th>\n",
       "      <th>EVBAP_Latest</th>\n",
       "      <th>EVBAP_Max</th>\n",
       "      <th>EVBAP_Min</th>\n",
       "      <th>EVCCS</th>\n",
       "      <th>EVCM1</th>\n",
       "      <th>EVCTM</th>\n",
       "      <th>EVCCU</th>\n",
       "      <th>EVCSD</th>\n",
       "      <th>EVVCE</th>\n",
       "      <th>EVPSC_Latest</th>\n",
       "      <th>EVPSC_Max</th>\n",
       "      <th>EVPSC_Min</th>\n",
       "      <th>EVVOU</th>\n",
       "      <th>EVCOU</th>\n",
       "      <th>EVCPV</th>\n",
       "      <th>EVVCD</th>\n",
       "      <th>EVCCD</th>\n",
       "      <th>EVCSC</th>\n",
       "      <th>EVEST</th>\n",
       "      <th>EVCHS</th>\n",
       "      <th>EVR10</th>\n",
       "      <th>EVRMN</th>\n",
       "      <th>EVHVS</th>\n",
       "      <th>EVV12</th>\n",
       "      <th>EVPWA_MAX</th>\n",
       "      <th>EVPWA_MIN</th>\n",
       "      <th>EVMCV_MAX</th>\n",
       "      <th>EVMCV_MIN</th>\n",
       "      <th>EVSMA_MAX</th>\n",
       "      <th>EVSMA_MIN</th>\n",
       "      <th>EVSMI_MAX</th>\n",
       "      <th>EVSMI_MIN</th>\n",
       "      <th>EVSOH</th>\n",
       "      <th>EVBMA_Latest</th>\n",
       "      <th>EVBMA_Max</th>\n",
       "      <th>EVBMA_Min</th>\n",
       "      <th>EVBMI_Latest</th>\n",
       "      <th>EVBMI_Max</th>\n",
       "      <th>EVBMI_Min</th>\n",
       "      <th>EVBOA_AVG</th>\n",
       "      <th>EVBOA_MAX</th>\n",
       "      <th>EVBOA_MIN</th>\n",
       "      <th>EVBOV_AVG</th>\n",
       "      <th>EVBOV_MAX</th>\n",
       "      <th>EVBOV_MIN</th>\n",
       "      <th>EVIRP</th>\n",
       "      <th>EVIRN</th>\n",
       "      <th>EVSOMA</th>\n",
       "      <th>EVSOMI</th>\n",
       "      <th>EVIGM_Latest</th>\n",
       "      <th>EVIGM_Max</th>\n",
       "      <th>EVIGM_Min</th>\n",
       "      <th>EVCOM_Latest</th>\n",
       "      <th>EVCOM_Max</th>\n",
       "      <th>EVCOM_Min</th>\n",
       "      <th>EVICO_Latest</th>\n",
       "      <th>EVICO_Max</th>\n",
       "      <th>EVICO_Min</th>\n",
       "      <th>EVIRT_Latest</th>\n",
       "      <th>EVIRT_Max</th>\n",
       "      <th>EVIRT_Min</th>\n",
       "      <th>EVIDC</th>\n",
       "      <th>EVMGT</th>\n",
       "      <th>EVMGS</th>\n",
       "      <th>EVMGF</th>\n",
       "      <th>EVMGR</th>\n",
       "      <th>EVIND</th>\n",
       "      <th>EVICM</th>\n",
       "      <th>EVCPW</th>\n",
       "      <th>EVCPF_Latest</th>\n",
       "      <th>EVCPF_Max</th>\n",
       "      <th>EVCPF_Min</th>\n",
       "      <th>EVCI1_Latest</th>\n",
       "      <th>EVCI1_Max</th>\n",
       "      <th>EVCI1_Min</th>\n",
       "      <th>EVCI2_Latest</th>\n",
       "      <th>EVCI2_Max</th>\n",
       "      <th>EVCI2_Min</th>\n",
       "      <th>EVCBD_Latest</th>\n",
       "      <th>EVCBD_Max</th>\n",
       "      <th>EVCBD_Min</th>\n",
       "      <th>EVCRP</th>\n",
       "      <th>EVACV_AVG</th>\n",
       "      <th>EVACV_Max</th>\n",
       "      <th>EVACV_Min</th>\n",
       "      <th>EVCDO_AVG</th>\n",
       "      <th>EVCDO_Max</th>\n",
       "      <th>EVCDO_Min</th>\n",
       "      <th>EVCCO_AVG</th>\n",
       "      <th>EVCCO_Max</th>\n",
       "      <th>EVCCO_Min</th>\n",
       "      <th>EVSDT</th>\n",
       "      <th>EVCHC</th>\n",
       "      <th>EVCHT_AVG</th>\n",
       "      <th>EVCHT_Max</th>\n",
       "      <th>EVCHT_Min</th>\n",
       "      <th>EVCHE</th>\n",
       "      <th>EVDI1</th>\n",
       "      <th>EVDI2</th>\n",
       "      <th>EVDIT</th>\n",
       "      <th>EVOII</th>\n",
       "      <th>EVDOA</th>\n",
       "      <th>EVDOV</th>\n",
       "      <th>EVDSE</th>\n",
       "      <th>EVACS</th>\n",
       "      <th>EVPSS</th>\n",
       "      <th>EVMSC</th>\n",
       "      <th>EVRER</th>\n",
       "      <th>EVDRV</th>\n",
       "      <th>EVMTR</th>\n",
       "      <th>EVODO</th>\n",
       "      <th>EVOAS</th>\n",
       "      <th>EVHTR</th>\n",
       "      <th>EVACE</th>\n",
       "      <th>EVTRE</th>\n",
       "      <th>EVCLC</th>\n",
       "      <th>EVBFN</th>\n",
       "      <th>EVIST</th>\n",
       "      <th>EVHTP_AVG</th>\n",
       "      <th>EVHTP_Max</th>\n",
       "      <th>EVHTP_Min</th>\n",
       "      <th>EVVBT</th>\n",
       "      <th>EVGSM</th>\n",
       "      <th>EVACO_X</th>\n",
       "      <th>EVACO_Y</th>\n",
       "      <th>EVACO_Z</th>\n",
       "      <th>Unnamed: 164</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>41398</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.04986</td>\n",
       "      <td>28.48182</td>\n",
       "      <td>191.97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547645638200</td>\n",
       "      <td>77.049833</td>\n",
       "      <td>28.481825</td>\n",
       "      <td>191.52437</td>\n",
       "      <td>762680892</td>\n",
       "      <td>3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>16</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>247</td>\n",
       "      <td>2.3281</td>\n",
       "      <td>71</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.025</td>\n",
       "      <td>4.025</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>100</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>4.25</td>\n",
       "      <td>5.25</td>\n",
       "      <td>3.5</td>\n",
       "      <td>266.00</td>\n",
       "      <td>266.25</td>\n",
       "      <td>266.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1850</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>28</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>80</td>\n",
       "      <td>22</td>\n",
       "      <td>4.00</td>\n",
       "      <td>33.5</td>\n",
       "      <td>149</td>\n",
       "      <td>179.8</td>\n",
       "      <td>-180.2</td>\n",
       "      <td>266</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.375</td>\n",
       "      <td>13.675</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2597</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>138</td>\n",
       "      <td>-57</td>\n",
       "      <td>-763</td>\n",
       "      <td>718</td>\n",
       "      <td>104</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41399</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.04986</td>\n",
       "      <td>28.48182</td>\n",
       "      <td>191.97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547645638300</td>\n",
       "      <td>77.049833</td>\n",
       "      <td>28.481825</td>\n",
       "      <td>191.52437</td>\n",
       "      <td>762680892</td>\n",
       "      <td>3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>16</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>247</td>\n",
       "      <td>2.3281</td>\n",
       "      <td>71</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.025</td>\n",
       "      <td>4.025</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>100</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>4.25</td>\n",
       "      <td>5.25</td>\n",
       "      <td>3.5</td>\n",
       "      <td>266.00</td>\n",
       "      <td>266.25</td>\n",
       "      <td>266.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1850</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>28</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>80</td>\n",
       "      <td>22</td>\n",
       "      <td>4.00</td>\n",
       "      <td>33.5</td>\n",
       "      <td>149</td>\n",
       "      <td>179.8</td>\n",
       "      <td>-180.2</td>\n",
       "      <td>266</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.375</td>\n",
       "      <td>13.675</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2597</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>138</td>\n",
       "      <td>-57</td>\n",
       "      <td>-763</td>\n",
       "      <td>718</td>\n",
       "      <td>104</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41400</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.04986</td>\n",
       "      <td>28.48182</td>\n",
       "      <td>191.97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547645638400</td>\n",
       "      <td>77.049833</td>\n",
       "      <td>28.481825</td>\n",
       "      <td>191.52437</td>\n",
       "      <td>762680892</td>\n",
       "      <td>3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>16</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>247</td>\n",
       "      <td>1.1016</td>\n",
       "      <td>113</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>60.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.030</td>\n",
       "      <td>4.025</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>100</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>-496.00</td>\n",
       "      <td>-343.0</td>\n",
       "      <td>266.25</td>\n",
       "      <td>178.00</td>\n",
       "      <td>16195.0</td>\n",
       "      <td>1820</td>\n",
       "      <td>1820</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>-50</td>\n",
       "      <td>-6</td>\n",
       "      <td>31</td>\n",
       "      <td>115</td>\n",
       "      <td>202</td>\n",
       "      <td>24</td>\n",
       "      <td>-50</td>\n",
       "      <td>16</td>\n",
       "      <td>27</td>\n",
       "      <td>128</td>\n",
       "      <td>212</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2.8</td>\n",
       "      <td>40</td>\n",
       "      <td>180.0</td>\n",
       "      <td>-180.0</td>\n",
       "      <td>266</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.375</td>\n",
       "      <td>14.500</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2597</td>\n",
       "      <td>16.5</td>\n",
       "      <td>0</td>\n",
       "      <td>8.7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>140</td>\n",
       "      <td>-65</td>\n",
       "      <td>-828</td>\n",
       "      <td>656</td>\n",
       "      <td>68</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41401</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.04986</td>\n",
       "      <td>28.48182</td>\n",
       "      <td>191.97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547645638500</td>\n",
       "      <td>77.049833</td>\n",
       "      <td>28.481825</td>\n",
       "      <td>191.52437</td>\n",
       "      <td>762680892</td>\n",
       "      <td>3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>16</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>247</td>\n",
       "      <td>1.1016</td>\n",
       "      <td>113</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>60.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.030</td>\n",
       "      <td>4.025</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>100</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>-496.00</td>\n",
       "      <td>-343.0</td>\n",
       "      <td>266.25</td>\n",
       "      <td>178.00</td>\n",
       "      <td>16195.0</td>\n",
       "      <td>1820</td>\n",
       "      <td>1820</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>-50</td>\n",
       "      <td>-6</td>\n",
       "      <td>31</td>\n",
       "      <td>115</td>\n",
       "      <td>202</td>\n",
       "      <td>24</td>\n",
       "      <td>-50</td>\n",
       "      <td>16</td>\n",
       "      <td>27</td>\n",
       "      <td>128</td>\n",
       "      <td>212</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2.8</td>\n",
       "      <td>40</td>\n",
       "      <td>180.0</td>\n",
       "      <td>-180.0</td>\n",
       "      <td>266</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.375</td>\n",
       "      <td>14.500</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2597</td>\n",
       "      <td>16.5</td>\n",
       "      <td>0</td>\n",
       "      <td>8.7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>140</td>\n",
       "      <td>-65</td>\n",
       "      <td>-828</td>\n",
       "      <td>656</td>\n",
       "      <td>68</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           mo                tp  dr        ln        lt  \\\n",
       "41398  DEFREG:358272088715191  Trip not started NaN  77.04986  28.48182   \n",
       "41399  DEFREG:358272088715191  Trip not started NaN  77.04986  28.48182   \n",
       "41400  DEFREG:358272088715191  Trip not started NaN  77.04986  28.48182   \n",
       "41401  DEFREG:358272088715191  Trip not started NaN  77.04986  28.48182   \n",
       "\n",
       "           hd  sp             tm         mn         mt         mh         ml  \\\n",
       "41398  191.97 NaN  1547645638200  77.049833  28.481825  191.52437  762680892   \n",
       "41399  191.97 NaN  1547645638300  77.049833  28.481825  191.52437  762680892   \n",
       "41400  191.97 NaN  1547645638400  77.049833  28.481825  191.52437  762680892   \n",
       "41401  191.97 NaN  1547645638500  77.049833  28.481825  191.52437  762680892   \n",
       "\n",
       "       mr  SpeedLimit  hdop  numsat             IMEI           trip_id EVTmg  \\\n",
       "41398   3        50.0   0.7      16  358272088715191  Trip not started     P   \n",
       "41399   3        50.0   0.7      16  358272088715191  Trip not started     P   \n",
       "41400   3        50.0   0.7      16  358272088715191  Trip not started     P   \n",
       "41401   3        50.0   0.7      16  358272088715191  Trip not started     P   \n",
       "\n",
       "            EVVer  EVCfg  EVIGS  EVIGC   EVVSP  EVDRG  EVGPO  EVBRP  EVCFN  \\\n",
       "41398  M1_POCEV.0    NaN      1    247  2.3281     71     11      0      1   \n",
       "41399  M1_POCEV.0    NaN      1    247  2.3281     71     11      0      1   \n",
       "41400  M1_POCEV.0    NaN      1    247  1.1016    113     11      0      0   \n",
       "41401  M1_POCEV.0    NaN      1    247  1.1016    113     11      0      0   \n",
       "\n",
       "       EVICR  EVTRQ  EVCST  EVDDC  EVBCA  EVBBV  EVDR1  EVDR2  EVRGT  EVACP  \\\n",
       "41398      1   28.7      1   13.9      0   47.0      0      0      0    0.0   \n",
       "41399      1   28.7      1   13.9      0   47.0      0      0      0    0.0   \n",
       "41400      1    5.0      1   13.9      0   60.5      0      0      0    0.0   \n",
       "41401      1    5.0      1   13.9      0   60.5      0      0      0    0.0   \n",
       "\n",
       "       EVBAP_Latest  EVBAP_Max  EVBAP_Min  EVCCS  EVCM1  EVCTM  EVCCU  EVCSD  \\\n",
       "41398             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "41399             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "41400             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "41401             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "\n",
       "       EVVCE  EVPSC_Latest  EVPSC_Max  EVPSC_Min  EVVOU  EVCOU  EVCPV  EVVCD  \\\n",
       "41398    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "41399    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "41400    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "41401    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "\n",
       "       EVCCD  EVCSC  EVEST  EVCHS  EVR10  EVRMN  EVHVS  EVV12  EVPWA_MAX  \\\n",
       "41398    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "41399    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "41400    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "41401    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "\n",
       "       EVPWA_MIN  EVMCV_MAX  EVMCV_MIN  EVSMA_MAX  EVSMA_MIN  EVSMI_MAX  \\\n",
       "41398          0      4.025      4.025       89.2       89.2       89.0   \n",
       "41399          0      4.025      4.025       89.2       89.2       89.0   \n",
       "41400          0      4.030      4.025       89.2       89.2       89.0   \n",
       "41401          0      4.030      4.025       89.2       89.2       89.0   \n",
       "\n",
       "       EVSMI_MIN  EVSOH  EVBMA_Latest  EVBMA_Max  EVBMA_Min  EVBMI_Latest  \\\n",
       "41398       89.0    100          19.0       19.0       19.0          18.0   \n",
       "41399       89.0    100          19.0       19.0       19.0          18.0   \n",
       "41400       89.0    100          19.0       19.0       19.0          18.0   \n",
       "41401       89.0    100          19.0       19.0       19.0          18.0   \n",
       "\n",
       "       EVBMI_Max  EVBMI_Min  EVBOA_AVG  EVBOA_MAX  EVBOA_MIN  EVBOV_AVG  \\\n",
       "41398       18.0       18.0       4.25       5.25        3.5     266.00   \n",
       "41399       18.0       18.0       4.25       5.25        3.5     266.00   \n",
       "41400       18.0       18.0       2.00    -496.00     -343.0     266.25   \n",
       "41401       18.0       18.0       2.00    -496.00     -343.0     266.25   \n",
       "\n",
       "       EVBOV_MAX  EVBOV_MIN  EVIRP  EVIRN  EVSOMA  EVSOMI  EVIGM_Latest  \\\n",
       "41398     266.25      266.0   1790   1850     100     100            28   \n",
       "41399     266.25      266.0   1790   1850     100     100            28   \n",
       "41400     178.00    16195.0   1820   1820     100     100            25   \n",
       "41401     178.00    16195.0   1820   1820     100     100            25   \n",
       "\n",
       "       EVIGM_Max  EVIGM_Min  EVCOM_Latest  EVCOM_Max  EVCOM_Min  EVICO_Latest  \\\n",
       "41398         47          0            31         36          0            24   \n",
       "41399         47          0            31         36          0            24   \n",
       "41400        -50         -6            31        115        202            24   \n",
       "41401        -50         -6            31        115        202            24   \n",
       "\n",
       "       EVICO_Max  EVICO_Min  EVIRT_Latest  EVIRT_Max  EVIRT_Min  EVIDC  EVMGT  \\\n",
       "41398         26          0            27         80         22   4.00   33.5   \n",
       "41399         26          0            27         80         22   4.00   33.5   \n",
       "41400        -50         16            27        128        212   0.25    2.8   \n",
       "41401        -50         16            27        128        212   0.25    2.8   \n",
       "\n",
       "       EVMGS  EVMGF  EVMGR  EVIND  EVICM  EVCPW  EVCPF_Latest  EVCPF_Max  \\\n",
       "41398    149  179.8 -180.2    266      8    NaN           NaN        NaN   \n",
       "41399    149  179.8 -180.2    266      8    NaN           NaN        NaN   \n",
       "41400     40  180.0 -180.0    266      8    NaN           NaN        NaN   \n",
       "41401     40  180.0 -180.0    266      8    NaN           NaN        NaN   \n",
       "\n",
       "       EVCPF_Min  EVCI1_Latest  EVCI1_Max  EVCI1_Min  EVCI2_Latest  EVCI2_Max  \\\n",
       "41398        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "41399        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "41400        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "41401        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "\n",
       "       EVCI2_Min  EVCBD_Latest  EVCBD_Max  EVCBD_Min  EVCRP  EVACV_AVG  \\\n",
       "41398        NaN           NaN        NaN        NaN      1        NaN   \n",
       "41399        NaN           NaN        NaN        NaN      1        NaN   \n",
       "41400        NaN           NaN        NaN        NaN      1        NaN   \n",
       "41401        NaN           NaN        NaN        NaN      1        NaN   \n",
       "\n",
       "       EVACV_Max  EVACV_Min  EVCDO_AVG  EVCDO_Max  EVCDO_Min  EVCCO_AVG  \\\n",
       "41398        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "41399        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "41400        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "41401        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "\n",
       "       EVCCO_Max  EVCCO_Min  EVSDT  EVCHC  EVCHT_AVG  EVCHT_Max  EVCHT_Min  \\\n",
       "41398        NaN        NaN    NaN    NaN        NaN        NaN        NaN   \n",
       "41399        NaN        NaN    NaN    NaN        NaN        NaN        NaN   \n",
       "41400        NaN        NaN    NaN    NaN        NaN        NaN        NaN   \n",
       "41401        NaN        NaN    NaN    NaN        NaN        NaN        NaN   \n",
       "\n",
       "       EVCHE  EVDI1  EVDI2  EVDIT  EVOII  EVDOA  EVDOV  EVDSE  EVACS   EVPSS  \\\n",
       "41398    NaN     29     30     26      0     13   13.9      0  0.375  13.675   \n",
       "41399    NaN     29     30     26      0     13   13.9      0  0.375  13.675   \n",
       "41400    NaN     29     30     26      0     30   13.9      0 -0.375  14.500   \n",
       "41401    NaN     29     30     26      0     30   13.9      0 -0.375  14.500   \n",
       "\n",
       "       EVMSC  EVRER  EVDRV  EVMTR  EVODO  EVOAS  EVHTR  EVACE  EVTRE  EVCLC  \\\n",
       "41398    2.3      0 -65532      0   2597   16.0      0    8.9   50.0     55   \n",
       "41399    2.3      0 -65532      0   2597   16.0      0    8.9   50.0     55   \n",
       "41400    0.5      0 -65532      0   2597   16.5      0    8.7   50.0     55   \n",
       "41401    0.5      0 -65532      0   2597   16.5      0    8.7   50.0     55   \n",
       "\n",
       "       EVBFN  EVIST  EVHTP_AVG  EVHTP_Max  EVHTP_Min  EVVBT  EVGSM  EVACO_X  \\\n",
       "41398      0      0          0          0          0    138    -57     -763   \n",
       "41399      0      0          0          0          0    138    -57     -763   \n",
       "41400      0      0          0          0          0    140    -65     -828   \n",
       "41401      0      0          0          0          0    140    -65     -828   \n",
       "\n",
       "       EVACO_Y  EVACO_Z  Unnamed: 164  \n",
       "41398      718      104           NaN  \n",
       "41399      718      104           NaN  \n",
       "41400      656       68           NaN  \n",
       "41401      656       68           NaN  "
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# cross-checking the logic\n",
    "data[41398:41402]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating the new data set t_data. This data contains value for single trip only.\n",
    "t_data = data[:41400]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mo</th>\n",
       "      <th>tp</th>\n",
       "      <th>dr</th>\n",
       "      <th>ln</th>\n",
       "      <th>lt</th>\n",
       "      <th>hd</th>\n",
       "      <th>sp</th>\n",
       "      <th>tm</th>\n",
       "      <th>mn</th>\n",
       "      <th>mt</th>\n",
       "      <th>mh</th>\n",
       "      <th>ml</th>\n",
       "      <th>mr</th>\n",
       "      <th>SpeedLimit</th>\n",
       "      <th>hdop</th>\n",
       "      <th>numsat</th>\n",
       "      <th>IMEI</th>\n",
       "      <th>trip_id</th>\n",
       "      <th>EVTmg</th>\n",
       "      <th>EVVer</th>\n",
       "      <th>EVCfg</th>\n",
       "      <th>EVIGS</th>\n",
       "      <th>EVIGC</th>\n",
       "      <th>EVVSP</th>\n",
       "      <th>EVDRG</th>\n",
       "      <th>EVGPO</th>\n",
       "      <th>EVBRP</th>\n",
       "      <th>EVCFN</th>\n",
       "      <th>EVICR</th>\n",
       "      <th>EVTRQ</th>\n",
       "      <th>EVCST</th>\n",
       "      <th>EVDDC</th>\n",
       "      <th>EVBCA</th>\n",
       "      <th>EVBBV</th>\n",
       "      <th>EVDR1</th>\n",
       "      <th>EVDR2</th>\n",
       "      <th>EVRGT</th>\n",
       "      <th>EVACP</th>\n",
       "      <th>EVBAP_Latest</th>\n",
       "      <th>EVBAP_Max</th>\n",
       "      <th>EVBAP_Min</th>\n",
       "      <th>EVCCS</th>\n",
       "      <th>EVCM1</th>\n",
       "      <th>EVCTM</th>\n",
       "      <th>EVCCU</th>\n",
       "      <th>EVCSD</th>\n",
       "      <th>EVVCE</th>\n",
       "      <th>EVPSC_Latest</th>\n",
       "      <th>EVPSC_Max</th>\n",
       "      <th>EVPSC_Min</th>\n",
       "      <th>EVVOU</th>\n",
       "      <th>EVCOU</th>\n",
       "      <th>EVCPV</th>\n",
       "      <th>EVVCD</th>\n",
       "      <th>EVCCD</th>\n",
       "      <th>EVCSC</th>\n",
       "      <th>EVEST</th>\n",
       "      <th>EVCHS</th>\n",
       "      <th>EVR10</th>\n",
       "      <th>EVRMN</th>\n",
       "      <th>EVHVS</th>\n",
       "      <th>EVV12</th>\n",
       "      <th>EVPWA_MAX</th>\n",
       "      <th>EVPWA_MIN</th>\n",
       "      <th>EVMCV_MAX</th>\n",
       "      <th>EVMCV_MIN</th>\n",
       "      <th>EVSMA_MAX</th>\n",
       "      <th>EVSMA_MIN</th>\n",
       "      <th>EVSMI_MAX</th>\n",
       "      <th>EVSMI_MIN</th>\n",
       "      <th>EVSOH</th>\n",
       "      <th>EVBMA_Latest</th>\n",
       "      <th>EVBMA_Max</th>\n",
       "      <th>EVBMA_Min</th>\n",
       "      <th>EVBMI_Latest</th>\n",
       "      <th>EVBMI_Max</th>\n",
       "      <th>EVBMI_Min</th>\n",
       "      <th>EVBOA_AVG</th>\n",
       "      <th>EVBOA_MAX</th>\n",
       "      <th>EVBOA_MIN</th>\n",
       "      <th>EVBOV_AVG</th>\n",
       "      <th>EVBOV_MAX</th>\n",
       "      <th>EVBOV_MIN</th>\n",
       "      <th>EVIRP</th>\n",
       "      <th>EVIRN</th>\n",
       "      <th>EVSOMA</th>\n",
       "      <th>EVSOMI</th>\n",
       "      <th>EVIGM_Latest</th>\n",
       "      <th>EVIGM_Max</th>\n",
       "      <th>EVIGM_Min</th>\n",
       "      <th>EVCOM_Latest</th>\n",
       "      <th>EVCOM_Max</th>\n",
       "      <th>EVCOM_Min</th>\n",
       "      <th>EVICO_Latest</th>\n",
       "      <th>EVICO_Max</th>\n",
       "      <th>EVICO_Min</th>\n",
       "      <th>EVIRT_Latest</th>\n",
       "      <th>EVIRT_Max</th>\n",
       "      <th>EVIRT_Min</th>\n",
       "      <th>EVIDC</th>\n",
       "      <th>EVMGT</th>\n",
       "      <th>EVMGS</th>\n",
       "      <th>EVMGF</th>\n",
       "      <th>EVMGR</th>\n",
       "      <th>EVIND</th>\n",
       "      <th>EVICM</th>\n",
       "      <th>EVCPW</th>\n",
       "      <th>EVCPF_Latest</th>\n",
       "      <th>EVCPF_Max</th>\n",
       "      <th>EVCPF_Min</th>\n",
       "      <th>EVCI1_Latest</th>\n",
       "      <th>EVCI1_Max</th>\n",
       "      <th>EVCI1_Min</th>\n",
       "      <th>EVCI2_Latest</th>\n",
       "      <th>EVCI2_Max</th>\n",
       "      <th>EVCI2_Min</th>\n",
       "      <th>EVCBD_Latest</th>\n",
       "      <th>EVCBD_Max</th>\n",
       "      <th>EVCBD_Min</th>\n",
       "      <th>EVCRP</th>\n",
       "      <th>EVACV_AVG</th>\n",
       "      <th>EVACV_Max</th>\n",
       "      <th>EVACV_Min</th>\n",
       "      <th>EVCDO_AVG</th>\n",
       "      <th>EVCDO_Max</th>\n",
       "      <th>EVCDO_Min</th>\n",
       "      <th>EVCCO_AVG</th>\n",
       "      <th>EVCCO_Max</th>\n",
       "      <th>EVCCO_Min</th>\n",
       "      <th>EVSDT</th>\n",
       "      <th>EVCHC</th>\n",
       "      <th>EVCHT_AVG</th>\n",
       "      <th>EVCHT_Max</th>\n",
       "      <th>EVCHT_Min</th>\n",
       "      <th>EVCHE</th>\n",
       "      <th>EVDI1</th>\n",
       "      <th>EVDI2</th>\n",
       "      <th>EVDIT</th>\n",
       "      <th>EVOII</th>\n",
       "      <th>EVDOA</th>\n",
       "      <th>EVDOV</th>\n",
       "      <th>EVDSE</th>\n",
       "      <th>EVACS</th>\n",
       "      <th>EVPSS</th>\n",
       "      <th>EVMSC</th>\n",
       "      <th>EVRER</th>\n",
       "      <th>EVDRV</th>\n",
       "      <th>EVMTR</th>\n",
       "      <th>EVODO</th>\n",
       "      <th>EVOAS</th>\n",
       "      <th>EVHTR</th>\n",
       "      <th>EVACE</th>\n",
       "      <th>EVTRE</th>\n",
       "      <th>EVCLC</th>\n",
       "      <th>EVBFN</th>\n",
       "      <th>EVIST</th>\n",
       "      <th>EVHTP_AVG</th>\n",
       "      <th>EVHTP_Max</th>\n",
       "      <th>EVHTP_Min</th>\n",
       "      <th>EVVBT</th>\n",
       "      <th>EVGSM</th>\n",
       "      <th>EVACO_X</th>\n",
       "      <th>EVACO_Y</th>\n",
       "      <th>EVACO_Z</th>\n",
       "      <th>Unnamed: 164</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>41395</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.04986</td>\n",
       "      <td>28.48182</td>\n",
       "      <td>191.97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547645637900</td>\n",
       "      <td>77.049833</td>\n",
       "      <td>28.481825</td>\n",
       "      <td>191.52437</td>\n",
       "      <td>762680892</td>\n",
       "      <td>3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>16</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>247</td>\n",
       "      <td>2.3281</td>\n",
       "      <td>71</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.025</td>\n",
       "      <td>4.025</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>100</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>4.25</td>\n",
       "      <td>5.25</td>\n",
       "      <td>3.5</td>\n",
       "      <td>266.0</td>\n",
       "      <td>266.25</td>\n",
       "      <td>266.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1850</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>28</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>80</td>\n",
       "      <td>22</td>\n",
       "      <td>4.0</td>\n",
       "      <td>33.5</td>\n",
       "      <td>149</td>\n",
       "      <td>179.8</td>\n",
       "      <td>-180.2</td>\n",
       "      <td>266</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.375</td>\n",
       "      <td>13.675</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2597</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>138</td>\n",
       "      <td>-57</td>\n",
       "      <td>-763</td>\n",
       "      <td>718</td>\n",
       "      <td>104</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41396</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.04986</td>\n",
       "      <td>28.48182</td>\n",
       "      <td>191.97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547645638000</td>\n",
       "      <td>77.049833</td>\n",
       "      <td>28.481825</td>\n",
       "      <td>191.52437</td>\n",
       "      <td>762680892</td>\n",
       "      <td>3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>16</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>247</td>\n",
       "      <td>2.3281</td>\n",
       "      <td>71</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.025</td>\n",
       "      <td>4.025</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>100</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>4.25</td>\n",
       "      <td>5.25</td>\n",
       "      <td>3.5</td>\n",
       "      <td>266.0</td>\n",
       "      <td>266.25</td>\n",
       "      <td>266.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1850</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>28</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>80</td>\n",
       "      <td>22</td>\n",
       "      <td>4.0</td>\n",
       "      <td>33.5</td>\n",
       "      <td>149</td>\n",
       "      <td>179.8</td>\n",
       "      <td>-180.2</td>\n",
       "      <td>266</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.375</td>\n",
       "      <td>13.675</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2597</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>138</td>\n",
       "      <td>-57</td>\n",
       "      <td>-763</td>\n",
       "      <td>718</td>\n",
       "      <td>104</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41397</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.04986</td>\n",
       "      <td>28.48182</td>\n",
       "      <td>191.97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547645638100</td>\n",
       "      <td>77.049833</td>\n",
       "      <td>28.481825</td>\n",
       "      <td>191.52437</td>\n",
       "      <td>762680892</td>\n",
       "      <td>3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>16</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>247</td>\n",
       "      <td>2.3281</td>\n",
       "      <td>71</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.025</td>\n",
       "      <td>4.025</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>100</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>4.25</td>\n",
       "      <td>5.25</td>\n",
       "      <td>3.5</td>\n",
       "      <td>266.0</td>\n",
       "      <td>266.25</td>\n",
       "      <td>266.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1850</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>28</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>80</td>\n",
       "      <td>22</td>\n",
       "      <td>4.0</td>\n",
       "      <td>33.5</td>\n",
       "      <td>149</td>\n",
       "      <td>179.8</td>\n",
       "      <td>-180.2</td>\n",
       "      <td>266</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.375</td>\n",
       "      <td>13.675</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2597</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>138</td>\n",
       "      <td>-57</td>\n",
       "      <td>-763</td>\n",
       "      <td>718</td>\n",
       "      <td>104</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41398</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.04986</td>\n",
       "      <td>28.48182</td>\n",
       "      <td>191.97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547645638200</td>\n",
       "      <td>77.049833</td>\n",
       "      <td>28.481825</td>\n",
       "      <td>191.52437</td>\n",
       "      <td>762680892</td>\n",
       "      <td>3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>16</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>247</td>\n",
       "      <td>2.3281</td>\n",
       "      <td>71</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.025</td>\n",
       "      <td>4.025</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>100</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>4.25</td>\n",
       "      <td>5.25</td>\n",
       "      <td>3.5</td>\n",
       "      <td>266.0</td>\n",
       "      <td>266.25</td>\n",
       "      <td>266.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1850</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>28</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>80</td>\n",
       "      <td>22</td>\n",
       "      <td>4.0</td>\n",
       "      <td>33.5</td>\n",
       "      <td>149</td>\n",
       "      <td>179.8</td>\n",
       "      <td>-180.2</td>\n",
       "      <td>266</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.375</td>\n",
       "      <td>13.675</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2597</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>138</td>\n",
       "      <td>-57</td>\n",
       "      <td>-763</td>\n",
       "      <td>718</td>\n",
       "      <td>104</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41399</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.04986</td>\n",
       "      <td>28.48182</td>\n",
       "      <td>191.97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547645638300</td>\n",
       "      <td>77.049833</td>\n",
       "      <td>28.481825</td>\n",
       "      <td>191.52437</td>\n",
       "      <td>762680892</td>\n",
       "      <td>3</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>16</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>247</td>\n",
       "      <td>2.3281</td>\n",
       "      <td>71</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.025</td>\n",
       "      <td>4.025</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.2</td>\n",
       "      <td>89.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>100</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>4.25</td>\n",
       "      <td>5.25</td>\n",
       "      <td>3.5</td>\n",
       "      <td>266.0</td>\n",
       "      <td>266.25</td>\n",
       "      <td>266.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1850</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>28</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>80</td>\n",
       "      <td>22</td>\n",
       "      <td>4.0</td>\n",
       "      <td>33.5</td>\n",
       "      <td>149</td>\n",
       "      <td>179.8</td>\n",
       "      <td>-180.2</td>\n",
       "      <td>266</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.375</td>\n",
       "      <td>13.675</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2597</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>138</td>\n",
       "      <td>-57</td>\n",
       "      <td>-763</td>\n",
       "      <td>718</td>\n",
       "      <td>104</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           mo                tp  dr        ln        lt  \\\n",
       "41395  DEFREG:358272088715191  Trip not started NaN  77.04986  28.48182   \n",
       "41396  DEFREG:358272088715191  Trip not started NaN  77.04986  28.48182   \n",
       "41397  DEFREG:358272088715191  Trip not started NaN  77.04986  28.48182   \n",
       "41398  DEFREG:358272088715191  Trip not started NaN  77.04986  28.48182   \n",
       "41399  DEFREG:358272088715191  Trip not started NaN  77.04986  28.48182   \n",
       "\n",
       "           hd  sp             tm         mn         mt         mh         ml  \\\n",
       "41395  191.97 NaN  1547645637900  77.049833  28.481825  191.52437  762680892   \n",
       "41396  191.97 NaN  1547645638000  77.049833  28.481825  191.52437  762680892   \n",
       "41397  191.97 NaN  1547645638100  77.049833  28.481825  191.52437  762680892   \n",
       "41398  191.97 NaN  1547645638200  77.049833  28.481825  191.52437  762680892   \n",
       "41399  191.97 NaN  1547645638300  77.049833  28.481825  191.52437  762680892   \n",
       "\n",
       "       mr  SpeedLimit  hdop  numsat             IMEI           trip_id EVTmg  \\\n",
       "41395   3        50.0   0.7      16  358272088715191  Trip not started     P   \n",
       "41396   3        50.0   0.7      16  358272088715191  Trip not started     P   \n",
       "41397   3        50.0   0.7      16  358272088715191  Trip not started     P   \n",
       "41398   3        50.0   0.7      16  358272088715191  Trip not started     P   \n",
       "41399   3        50.0   0.7      16  358272088715191  Trip not started     P   \n",
       "\n",
       "            EVVer  EVCfg  EVIGS  EVIGC   EVVSP  EVDRG  EVGPO  EVBRP  EVCFN  \\\n",
       "41395  M1_POCEV.0    NaN      1    247  2.3281     71     11      0      1   \n",
       "41396  M1_POCEV.0    NaN      1    247  2.3281     71     11      0      1   \n",
       "41397  M1_POCEV.0    NaN      1    247  2.3281     71     11      0      1   \n",
       "41398  M1_POCEV.0    NaN      1    247  2.3281     71     11      0      1   \n",
       "41399  M1_POCEV.0    NaN      1    247  2.3281     71     11      0      1   \n",
       "\n",
       "       EVICR  EVTRQ  EVCST  EVDDC  EVBCA  EVBBV  EVDR1  EVDR2  EVRGT  EVACP  \\\n",
       "41395      1   28.7      1   13.9      0   47.0      0      0      0    0.0   \n",
       "41396      1   28.7      1   13.9      0   47.0      0      0      0    0.0   \n",
       "41397      1   28.7      1   13.9      0   47.0      0      0      0    0.0   \n",
       "41398      1   28.7      1   13.9      0   47.0      0      0      0    0.0   \n",
       "41399      1   28.7      1   13.9      0   47.0      0      0      0    0.0   \n",
       "\n",
       "       EVBAP_Latest  EVBAP_Max  EVBAP_Min  EVCCS  EVCM1  EVCTM  EVCCU  EVCSD  \\\n",
       "41395             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "41396             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "41397             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "41398             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "41399             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "\n",
       "       EVVCE  EVPSC_Latest  EVPSC_Max  EVPSC_Min  EVVOU  EVCOU  EVCPV  EVVCD  \\\n",
       "41395    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "41396    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "41397    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "41398    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "41399    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "\n",
       "       EVCCD  EVCSC  EVEST  EVCHS  EVR10  EVRMN  EVHVS  EVV12  EVPWA_MAX  \\\n",
       "41395    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "41396    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "41397    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "41398    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "41399    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "\n",
       "       EVPWA_MIN  EVMCV_MAX  EVMCV_MIN  EVSMA_MAX  EVSMA_MIN  EVSMI_MAX  \\\n",
       "41395          0      4.025      4.025       89.2       89.2       89.0   \n",
       "41396          0      4.025      4.025       89.2       89.2       89.0   \n",
       "41397          0      4.025      4.025       89.2       89.2       89.0   \n",
       "41398          0      4.025      4.025       89.2       89.2       89.0   \n",
       "41399          0      4.025      4.025       89.2       89.2       89.0   \n",
       "\n",
       "       EVSMI_MIN  EVSOH  EVBMA_Latest  EVBMA_Max  EVBMA_Min  EVBMI_Latest  \\\n",
       "41395       89.0    100          19.0       19.0       19.0          18.0   \n",
       "41396       89.0    100          19.0       19.0       19.0          18.0   \n",
       "41397       89.0    100          19.0       19.0       19.0          18.0   \n",
       "41398       89.0    100          19.0       19.0       19.0          18.0   \n",
       "41399       89.0    100          19.0       19.0       19.0          18.0   \n",
       "\n",
       "       EVBMI_Max  EVBMI_Min  EVBOA_AVG  EVBOA_MAX  EVBOA_MIN  EVBOV_AVG  \\\n",
       "41395       18.0       18.0       4.25       5.25        3.5      266.0   \n",
       "41396       18.0       18.0       4.25       5.25        3.5      266.0   \n",
       "41397       18.0       18.0       4.25       5.25        3.5      266.0   \n",
       "41398       18.0       18.0       4.25       5.25        3.5      266.0   \n",
       "41399       18.0       18.0       4.25       5.25        3.5      266.0   \n",
       "\n",
       "       EVBOV_MAX  EVBOV_MIN  EVIRP  EVIRN  EVSOMA  EVSOMI  EVIGM_Latest  \\\n",
       "41395     266.25      266.0   1790   1850     100     100            28   \n",
       "41396     266.25      266.0   1790   1850     100     100            28   \n",
       "41397     266.25      266.0   1790   1850     100     100            28   \n",
       "41398     266.25      266.0   1790   1850     100     100            28   \n",
       "41399     266.25      266.0   1790   1850     100     100            28   \n",
       "\n",
       "       EVIGM_Max  EVIGM_Min  EVCOM_Latest  EVCOM_Max  EVCOM_Min  EVICO_Latest  \\\n",
       "41395         47          0            31         36          0            24   \n",
       "41396         47          0            31         36          0            24   \n",
       "41397         47          0            31         36          0            24   \n",
       "41398         47          0            31         36          0            24   \n",
       "41399         47          0            31         36          0            24   \n",
       "\n",
       "       EVICO_Max  EVICO_Min  EVIRT_Latest  EVIRT_Max  EVIRT_Min  EVIDC  EVMGT  \\\n",
       "41395         26          0            27         80         22    4.0   33.5   \n",
       "41396         26          0            27         80         22    4.0   33.5   \n",
       "41397         26          0            27         80         22    4.0   33.5   \n",
       "41398         26          0            27         80         22    4.0   33.5   \n",
       "41399         26          0            27         80         22    4.0   33.5   \n",
       "\n",
       "       EVMGS  EVMGF  EVMGR  EVIND  EVICM  EVCPW  EVCPF_Latest  EVCPF_Max  \\\n",
       "41395    149  179.8 -180.2    266      8    NaN           NaN        NaN   \n",
       "41396    149  179.8 -180.2    266      8    NaN           NaN        NaN   \n",
       "41397    149  179.8 -180.2    266      8    NaN           NaN        NaN   \n",
       "41398    149  179.8 -180.2    266      8    NaN           NaN        NaN   \n",
       "41399    149  179.8 -180.2    266      8    NaN           NaN        NaN   \n",
       "\n",
       "       EVCPF_Min  EVCI1_Latest  EVCI1_Max  EVCI1_Min  EVCI2_Latest  EVCI2_Max  \\\n",
       "41395        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "41396        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "41397        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "41398        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "41399        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "\n",
       "       EVCI2_Min  EVCBD_Latest  EVCBD_Max  EVCBD_Min  EVCRP  EVACV_AVG  \\\n",
       "41395        NaN           NaN        NaN        NaN      1        NaN   \n",
       "41396        NaN           NaN        NaN        NaN      1        NaN   \n",
       "41397        NaN           NaN        NaN        NaN      1        NaN   \n",
       "41398        NaN           NaN        NaN        NaN      1        NaN   \n",
       "41399        NaN           NaN        NaN        NaN      1        NaN   \n",
       "\n",
       "       EVACV_Max  EVACV_Min  EVCDO_AVG  EVCDO_Max  EVCDO_Min  EVCCO_AVG  \\\n",
       "41395        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "41396        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "41397        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "41398        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "41399        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "\n",
       "       EVCCO_Max  EVCCO_Min  EVSDT  EVCHC  EVCHT_AVG  EVCHT_Max  EVCHT_Min  \\\n",
       "41395        NaN        NaN    NaN    NaN        NaN        NaN        NaN   \n",
       "41396        NaN        NaN    NaN    NaN        NaN        NaN        NaN   \n",
       "41397        NaN        NaN    NaN    NaN        NaN        NaN        NaN   \n",
       "41398        NaN        NaN    NaN    NaN        NaN        NaN        NaN   \n",
       "41399        NaN        NaN    NaN    NaN        NaN        NaN        NaN   \n",
       "\n",
       "       EVCHE  EVDI1  EVDI2  EVDIT  EVOII  EVDOA  EVDOV  EVDSE  EVACS   EVPSS  \\\n",
       "41395    NaN     29     30     26      0     13   13.9      0  0.375  13.675   \n",
       "41396    NaN     29     30     26      0     13   13.9      0  0.375  13.675   \n",
       "41397    NaN     29     30     26      0     13   13.9      0  0.375  13.675   \n",
       "41398    NaN     29     30     26      0     13   13.9      0  0.375  13.675   \n",
       "41399    NaN     29     30     26      0     13   13.9      0  0.375  13.675   \n",
       "\n",
       "       EVMSC  EVRER  EVDRV  EVMTR  EVODO  EVOAS  EVHTR  EVACE  EVTRE  EVCLC  \\\n",
       "41395    2.3      0 -65532      0   2597   16.0      0    8.9   50.0     55   \n",
       "41396    2.3      0 -65532      0   2597   16.0      0    8.9   50.0     55   \n",
       "41397    2.3      0 -65532      0   2597   16.0      0    8.9   50.0     55   \n",
       "41398    2.3      0 -65532      0   2597   16.0      0    8.9   50.0     55   \n",
       "41399    2.3      0 -65532      0   2597   16.0      0    8.9   50.0     55   \n",
       "\n",
       "       EVBFN  EVIST  EVHTP_AVG  EVHTP_Max  EVHTP_Min  EVVBT  EVGSM  EVACO_X  \\\n",
       "41395      0      0          0          0          0    138    -57     -763   \n",
       "41396      0      0          0          0          0    138    -57     -763   \n",
       "41397      0      0          0          0          0    138    -57     -763   \n",
       "41398      0      0          0          0          0    138    -57     -763   \n",
       "41399      0      0          0          0          0    138    -57     -763   \n",
       "\n",
       "       EVACO_Y  EVACO_Z  Unnamed: 164  \n",
       "41395      718      104           NaN  \n",
       "41396      718      104           NaN  \n",
       "41397      718      104           NaN  \n",
       "41398      718      104           NaN  \n",
       "41399      718      104           NaN  "
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t_data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [],
   "source": [
    "# making a new column called elapsed column\n",
    "# logic = current timestamp - initial timestamp (timestamp from where trip started) \n",
    "\n",
    "elapsed_time = []\n",
    "for k in range(0, len(t_data)):\n",
    "    temp = t_data.tm[k] - t_data.tm[0]\n",
    "    elapsed_time.append(temp)\n",
    "    \n",
    "elapsed_tm = pd.DataFrame({\n",
    "    \"elapsed_tm\": elapsed_time\n",
    "})\n",
    "\n",
    "t_data = pd.concat((t_data, elapsed_tm), axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mo</th>\n",
       "      <th>tp</th>\n",
       "      <th>dr</th>\n",
       "      <th>ln</th>\n",
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       "      <th>hd</th>\n",
       "      <th>sp</th>\n",
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       "      <th>mr</th>\n",
       "      <th>SpeedLimit</th>\n",
       "      <th>hdop</th>\n",
       "      <th>numsat</th>\n",
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       "      <th>trip_id</th>\n",
       "      <th>EVTmg</th>\n",
       "      <th>EVVer</th>\n",
       "      <th>EVCfg</th>\n",
       "      <th>EVIGS</th>\n",
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       "      <th>EVVSP</th>\n",
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       "      <th>EVGPO</th>\n",
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       "      <th>EVBBV</th>\n",
       "      <th>EVDR1</th>\n",
       "      <th>EVDR2</th>\n",
       "      <th>EVRGT</th>\n",
       "      <th>EVACP</th>\n",
       "      <th>EVBAP_Latest</th>\n",
       "      <th>EVBAP_Max</th>\n",
       "      <th>EVBAP_Min</th>\n",
       "      <th>EVCCS</th>\n",
       "      <th>EVCM1</th>\n",
       "      <th>EVCTM</th>\n",
       "      <th>EVCCU</th>\n",
       "      <th>EVCSD</th>\n",
       "      <th>EVVCE</th>\n",
       "      <th>EVPSC_Latest</th>\n",
       "      <th>EVPSC_Max</th>\n",
       "      <th>EVPSC_Min</th>\n",
       "      <th>EVVOU</th>\n",
       "      <th>EVCOU</th>\n",
       "      <th>EVCPV</th>\n",
       "      <th>EVVCD</th>\n",
       "      <th>EVCCD</th>\n",
       "      <th>EVCSC</th>\n",
       "      <th>EVEST</th>\n",
       "      <th>EVCHS</th>\n",
       "      <th>EVR10</th>\n",
       "      <th>EVRMN</th>\n",
       "      <th>EVHVS</th>\n",
       "      <th>EVV12</th>\n",
       "      <th>EVPWA_MAX</th>\n",
       "      <th>EVPWA_MIN</th>\n",
       "      <th>EVMCV_MAX</th>\n",
       "      <th>EVMCV_MIN</th>\n",
       "      <th>EVSMA_MAX</th>\n",
       "      <th>EVSMA_MIN</th>\n",
       "      <th>EVSMI_MAX</th>\n",
       "      <th>EVSMI_MIN</th>\n",
       "      <th>EVSOH</th>\n",
       "      <th>EVBMA_Latest</th>\n",
       "      <th>EVBMA_Max</th>\n",
       "      <th>EVBMA_Min</th>\n",
       "      <th>EVBMI_Latest</th>\n",
       "      <th>EVBMI_Max</th>\n",
       "      <th>EVBMI_Min</th>\n",
       "      <th>EVBOA_AVG</th>\n",
       "      <th>EVBOA_MAX</th>\n",
       "      <th>EVBOA_MIN</th>\n",
       "      <th>EVBOV_AVG</th>\n",
       "      <th>EVBOV_MAX</th>\n",
       "      <th>EVBOV_MIN</th>\n",
       "      <th>EVIRP</th>\n",
       "      <th>EVIRN</th>\n",
       "      <th>EVSOMA</th>\n",
       "      <th>EVSOMI</th>\n",
       "      <th>EVIGM_Latest</th>\n",
       "      <th>EVIGM_Max</th>\n",
       "      <th>EVIGM_Min</th>\n",
       "      <th>EVCOM_Latest</th>\n",
       "      <th>EVCOM_Max</th>\n",
       "      <th>EVCOM_Min</th>\n",
       "      <th>EVICO_Latest</th>\n",
       "      <th>EVICO_Max</th>\n",
       "      <th>EVICO_Min</th>\n",
       "      <th>EVIRT_Latest</th>\n",
       "      <th>EVIRT_Max</th>\n",
       "      <th>EVIRT_Min</th>\n",
       "      <th>EVIDC</th>\n",
       "      <th>EVMGT</th>\n",
       "      <th>EVMGS</th>\n",
       "      <th>EVMGF</th>\n",
       "      <th>EVMGR</th>\n",
       "      <th>EVIND</th>\n",
       "      <th>EVICM</th>\n",
       "      <th>EVCPW</th>\n",
       "      <th>EVCPF_Latest</th>\n",
       "      <th>EVCPF_Max</th>\n",
       "      <th>EVCPF_Min</th>\n",
       "      <th>EVCI1_Latest</th>\n",
       "      <th>EVCI1_Max</th>\n",
       "      <th>EVCI1_Min</th>\n",
       "      <th>EVCI2_Latest</th>\n",
       "      <th>EVCI2_Max</th>\n",
       "      <th>EVCI2_Min</th>\n",
       "      <th>EVCBD_Latest</th>\n",
       "      <th>EVCBD_Max</th>\n",
       "      <th>EVCBD_Min</th>\n",
       "      <th>EVCRP</th>\n",
       "      <th>EVACV_AVG</th>\n",
       "      <th>EVACV_Max</th>\n",
       "      <th>EVACV_Min</th>\n",
       "      <th>EVCDO_AVG</th>\n",
       "      <th>EVCDO_Max</th>\n",
       "      <th>EVCDO_Min</th>\n",
       "      <th>EVCCO_AVG</th>\n",
       "      <th>EVCCO_Max</th>\n",
       "      <th>EVCCO_Min</th>\n",
       "      <th>EVSDT</th>\n",
       "      <th>EVCHC</th>\n",
       "      <th>EVCHT_AVG</th>\n",
       "      <th>EVCHT_Max</th>\n",
       "      <th>EVCHT_Min</th>\n",
       "      <th>EVCHE</th>\n",
       "      <th>EVDI1</th>\n",
       "      <th>EVDI2</th>\n",
       "      <th>EVDIT</th>\n",
       "      <th>EVOII</th>\n",
       "      <th>EVDOA</th>\n",
       "      <th>EVDOV</th>\n",
       "      <th>EVDSE</th>\n",
       "      <th>EVACS</th>\n",
       "      <th>EVPSS</th>\n",
       "      <th>EVMSC</th>\n",
       "      <th>EVRER</th>\n",
       "      <th>EVDRV</th>\n",
       "      <th>EVMTR</th>\n",
       "      <th>EVODO</th>\n",
       "      <th>EVOAS</th>\n",
       "      <th>EVHTR</th>\n",
       "      <th>EVACE</th>\n",
       "      <th>EVTRE</th>\n",
       "      <th>EVCLC</th>\n",
       "      <th>EVBFN</th>\n",
       "      <th>EVIST</th>\n",
       "      <th>EVHTP_AVG</th>\n",
       "      <th>EVHTP_Max</th>\n",
       "      <th>EVHTP_Min</th>\n",
       "      <th>EVVBT</th>\n",
       "      <th>EVGSM</th>\n",
       "      <th>EVACO_X</th>\n",
       "      <th>EVACO_Y</th>\n",
       "      <th>EVACO_Z</th>\n",
       "      <th>Unnamed: 164</th>\n",
       "      <th>elapsed_tm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
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       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547605702400</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>87.78603</td>\n",
       "      <td>1036056339</td>\n",
       "      <td>5</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
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       "      <td>1</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
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       "      <td>0</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.88</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.1</td>\n",
       "      <td>78.1</td>\n",
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       "      <td>15.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-505.0</td>\n",
       "      <td>-357.0</td>\n",
       "      <td>257.75</td>\n",
       "      <td>174.0</td>\n",
       "      <td>16180.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1790</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
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       "      <td>-50</td>\n",
       "      <td>-16</td>\n",
       "      <td>14</td>\n",
       "      <td>88</td>\n",
       "      <td>212</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.225</td>\n",
       "      <td>52.9</td>\n",
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       "      <td>0</td>\n",
       "      <td>2572</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>-820</td>\n",
       "      <td>654</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
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       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547605702500</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>87.78603</td>\n",
       "      <td>1036056339</td>\n",
       "      <td>5</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>246</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87</td>\n",
       "      <td>10</td>\n",
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       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>60.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.88</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.1</td>\n",
       "      <td>78.1</td>\n",
       "      <td>100</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-505.0</td>\n",
       "      <td>-357.0</td>\n",
       "      <td>257.75</td>\n",
       "      <td>174.0</td>\n",
       "      <td>16180.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1790</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "      <td>-50</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>106</td>\n",
       "      <td>202</td>\n",
       "      <td>15</td>\n",
       "      <td>-50</td>\n",
       "      <td>-16</td>\n",
       "      <td>14</td>\n",
       "      <td>88</td>\n",
       "      <td>212</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>260</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.225</td>\n",
       "      <td>52.9</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2572</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>-820</td>\n",
       "      <td>654</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547605702600</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>87.78603</td>\n",
       "      <td>1036056339</td>\n",
       "      <td>5</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>246</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>60.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.88</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.1</td>\n",
       "      <td>78.1</td>\n",
       "      <td>100</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-505.0</td>\n",
       "      <td>-357.0</td>\n",
       "      <td>257.75</td>\n",
       "      <td>174.0</td>\n",
       "      <td>16180.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1790</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "      <td>-50</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>106</td>\n",
       "      <td>202</td>\n",
       "      <td>15</td>\n",
       "      <td>-50</td>\n",
       "      <td>-16</td>\n",
       "      <td>14</td>\n",
       "      <td>88</td>\n",
       "      <td>212</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>260</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.225</td>\n",
       "      <td>52.9</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2572</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>-820</td>\n",
       "      <td>654</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547605702700</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>87.78603</td>\n",
       "      <td>1036056339</td>\n",
       "      <td>5</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>246</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>60.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.88</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.1</td>\n",
       "      <td>78.1</td>\n",
       "      <td>100</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-505.0</td>\n",
       "      <td>-357.0</td>\n",
       "      <td>257.75</td>\n",
       "      <td>174.0</td>\n",
       "      <td>16180.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1790</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "      <td>-50</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>106</td>\n",
       "      <td>202</td>\n",
       "      <td>15</td>\n",
       "      <td>-50</td>\n",
       "      <td>-16</td>\n",
       "      <td>14</td>\n",
       "      <td>88</td>\n",
       "      <td>212</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>260</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.225</td>\n",
       "      <td>52.9</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2572</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>-820</td>\n",
       "      <td>654</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DEFREG:358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>NaN</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1547605702800</td>\n",
       "      <td>76.951081</td>\n",
       "      <td>28.390039</td>\n",
       "      <td>87.78603</td>\n",
       "      <td>1036056339</td>\n",
       "      <td>5</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7</td>\n",
       "      <td>358272088715191</td>\n",
       "      <td>Trip not started</td>\n",
       "      <td>P</td>\n",
       "      <td>M1_POCEV.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>246</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>60.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.88</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "      <td>78.1</td>\n",
       "      <td>78.1</td>\n",
       "      <td>100</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-505.0</td>\n",
       "      <td>-357.0</td>\n",
       "      <td>257.75</td>\n",
       "      <td>174.0</td>\n",
       "      <td>16180.0</td>\n",
       "      <td>1790</td>\n",
       "      <td>1790</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "      <td>-50</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>106</td>\n",
       "      <td>202</td>\n",
       "      <td>15</td>\n",
       "      <td>-50</td>\n",
       "      <td>-16</td>\n",
       "      <td>14</td>\n",
       "      <td>88</td>\n",
       "      <td>212</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>260</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>13.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.225</td>\n",
       "      <td>52.9</td>\n",
       "      <td>0</td>\n",
       "      <td>-65532</td>\n",
       "      <td>0</td>\n",
       "      <td>2572</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.7</td>\n",
       "      <td>50.0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>-820</td>\n",
       "      <td>654</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       mo                tp  dr         ln         lt   hd  \\\n",
       "0  DEFREG:358272088715191  Trip not started NaN  76.951081  28.390039  1.0   \n",
       "1  DEFREG:358272088715191  Trip not started NaN  76.951081  28.390039  1.0   \n",
       "2  DEFREG:358272088715191  Trip not started NaN  76.951081  28.390039  1.0   \n",
       "3  DEFREG:358272088715191  Trip not started NaN  76.951081  28.390039  1.0   \n",
       "4  DEFREG:358272088715191  Trip not started NaN  76.951081  28.390039  1.0   \n",
       "\n",
       "   sp             tm         mn         mt        mh          ml  mr  \\\n",
       "0 NaN  1547605702400  76.951081  28.390039  87.78603  1036056339   5   \n",
       "1 NaN  1547605702500  76.951081  28.390039  87.78603  1036056339   5   \n",
       "2 NaN  1547605702600  76.951081  28.390039  87.78603  1036056339   5   \n",
       "3 NaN  1547605702700  76.951081  28.390039  87.78603  1036056339   5   \n",
       "4 NaN  1547605702800  76.951081  28.390039  87.78603  1036056339   5   \n",
       "\n",
       "   SpeedLimit  hdop  numsat             IMEI           trip_id EVTmg  \\\n",
       "0        30.0   1.8       7  358272088715191  Trip not started     P   \n",
       "1        30.0   1.8       7  358272088715191  Trip not started     P   \n",
       "2        30.0   1.8       7  358272088715191  Trip not started     P   \n",
       "3        30.0   1.8       7  358272088715191  Trip not started     P   \n",
       "4        30.0   1.8       7  358272088715191  Trip not started     P   \n",
       "\n",
       "        EVVer  EVCfg  EVIGS  EVIGC  EVVSP  EVDRG  EVGPO  EVBRP  EVCFN  EVICR  \\\n",
       "0  M1_POCEV.0    NaN      1    246    0.0     87     10      0      0      1   \n",
       "1  M1_POCEV.0    NaN      1    246    0.0     87     10      0      0      1   \n",
       "2  M1_POCEV.0    NaN      1    246    0.0     87     10      0      0      1   \n",
       "3  M1_POCEV.0    NaN      1    246    0.0     87     10      0      0      1   \n",
       "4  M1_POCEV.0    NaN      1    246    0.0     87     10      0      0      1   \n",
       "\n",
       "   EVTRQ  EVCST  EVDDC  EVBCA  EVBBV  EVDR1  EVDR2  EVRGT  EVACP  \\\n",
       "0    0.0      1   13.9      0   60.5      0      0      0    0.0   \n",
       "1    0.0      1   13.9      0   60.5      0      0      0    0.0   \n",
       "2    0.0      1   13.9      0   60.5      0      0      0    0.0   \n",
       "3    0.0      1   13.9      0   60.5      0      0      0    0.0   \n",
       "4    0.0      1   13.9      0   60.5      0      0      0    0.0   \n",
       "\n",
       "   EVBAP_Latest  EVBAP_Max  EVBAP_Min  EVCCS  EVCM1  EVCTM  EVCCU  EVCSD  \\\n",
       "0             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "1             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "2             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "3             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "4             0          0          0      0    NaN    NaN    NaN    NaN   \n",
       "\n",
       "   EVVCE  EVPSC_Latest  EVPSC_Max  EVPSC_Min  EVVOU  EVCOU  EVCPV  EVVCD  \\\n",
       "0    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "1    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "2    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "3    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "4    NaN           NaN        NaN        NaN    NaN    NaN    NaN    NaN   \n",
       "\n",
       "   EVCCD  EVCSC  EVEST  EVCHS  EVR10  EVRMN  EVHVS  EVV12  EVPWA_MAX  \\\n",
       "0    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "1    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "2    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "3    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "4    NaN    NaN    NaN    NaN    NaN    NaN     10   13.8          0   \n",
       "\n",
       "   EVPWA_MIN  EVMCV_MAX  EVMCV_MIN  EVSMA_MAX  EVSMA_MIN  EVSMI_MAX  \\\n",
       "0          0       3.89       3.88       78.4       78.4       78.1   \n",
       "1          0       3.89       3.88       78.4       78.4       78.1   \n",
       "2          0       3.89       3.88       78.4       78.4       78.1   \n",
       "3          0       3.89       3.88       78.4       78.4       78.1   \n",
       "4          0       3.89       3.88       78.4       78.4       78.1   \n",
       "\n",
       "   EVSMI_MIN  EVSOH  EVBMA_Latest  EVBMA_Max  EVBMA_Min  EVBMI_Latest  \\\n",
       "0       78.1    100          15.5       15.5       15.5          15.0   \n",
       "1       78.1    100          15.5       15.5       15.5          15.0   \n",
       "2       78.1    100          15.5       15.5       15.5          15.0   \n",
       "3       78.1    100          15.5       15.5       15.5          15.0   \n",
       "4       78.1    100          15.5       15.5       15.5          15.0   \n",
       "\n",
       "   EVBMI_Max  EVBMI_Min  EVBOA_AVG  EVBOA_MAX  EVBOA_MIN  EVBOV_AVG  \\\n",
       "0       15.0       15.0        0.5     -505.0     -357.0     257.75   \n",
       "1       15.0       15.0        0.5     -505.0     -357.0     257.75   \n",
       "2       15.0       15.0        0.5     -505.0     -357.0     257.75   \n",
       "3       15.0       15.0        0.5     -505.0     -357.0     257.75   \n",
       "4       15.0       15.0        0.5     -505.0     -357.0     257.75   \n",
       "\n",
       "   EVBOV_MAX  EVBOV_MIN  EVIRP  EVIRN  EVSOMA  EVSOMI  EVIGM_Latest  \\\n",
       "0      174.0    16180.0   1790   1790     100     100            14   \n",
       "1      174.0    16180.0   1790   1790     100     100            14   \n",
       "2      174.0    16180.0   1790   1790     100     100            14   \n",
       "3      174.0    16180.0   1790   1790     100     100            14   \n",
       "4      174.0    16180.0   1790   1790     100     100            14   \n",
       "\n",
       "   EVIGM_Max  EVIGM_Min  EVCOM_Latest  EVCOM_Max  EVCOM_Min  EVICO_Latest  \\\n",
       "0        -50          2            14        106        202            15   \n",
       "1        -50          2            14        106        202            15   \n",
       "2        -50          2            14        106        202            15   \n",
       "3        -50          2            14        106        202            15   \n",
       "4        -50          2            14        106        202            15   \n",
       "\n",
       "   EVICO_Max  EVICO_Min  EVIRT_Latest  EVIRT_Max  EVIRT_Min  EVIDC  EVMGT  \\\n",
       "0        -50        -16            14         88        212    0.0   -0.1   \n",
       "1        -50        -16            14         88        212    0.0   -0.1   \n",
       "2        -50        -16            14         88        212    0.0   -0.1   \n",
       "3        -50        -16            14         88        212    0.0   -0.1   \n",
       "4        -50        -16            14         88        212    0.0   -0.1   \n",
       "\n",
       "   EVMGS  EVMGF  EVMGR  EVIND  EVICM  EVCPW  EVCPF_Latest  EVCPF_Max  \\\n",
       "0      0    0.0    0.0    260      3    NaN           NaN        NaN   \n",
       "1      0    0.0    0.0    260      3    NaN           NaN        NaN   \n",
       "2      0    0.0    0.0    260      3    NaN           NaN        NaN   \n",
       "3      0    0.0    0.0    260      3    NaN           NaN        NaN   \n",
       "4      0    0.0    0.0    260      3    NaN           NaN        NaN   \n",
       "\n",
       "   EVCPF_Min  EVCI1_Latest  EVCI1_Max  EVCI1_Min  EVCI2_Latest  EVCI2_Max  \\\n",
       "0        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "1        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "2        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "3        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "4        NaN           NaN        NaN        NaN           NaN        NaN   \n",
       "\n",
       "   EVCI2_Min  EVCBD_Latest  EVCBD_Max  EVCBD_Min  EVCRP  EVACV_AVG  EVACV_Max  \\\n",
       "0        NaN           NaN        NaN        NaN      1        NaN        NaN   \n",
       "1        NaN           NaN        NaN        NaN      1        NaN        NaN   \n",
       "2        NaN           NaN        NaN        NaN      1        NaN        NaN   \n",
       "3        NaN           NaN        NaN        NaN      1        NaN        NaN   \n",
       "4        NaN           NaN        NaN        NaN      1        NaN        NaN   \n",
       "\n",
       "   EVACV_Min  EVCDO_AVG  EVCDO_Max  EVCDO_Min  EVCCO_AVG  EVCCO_Max  \\\n",
       "0        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "1        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "2        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "3        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "4        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "\n",
       "   EVCCO_Min  EVSDT  EVCHC  EVCHT_AVG  EVCHT_Max  EVCHT_Min  EVCHE  EVDI1  \\\n",
       "0        NaN    NaN    NaN        NaN        NaN        NaN    NaN     15   \n",
       "1        NaN    NaN    NaN        NaN        NaN        NaN    NaN     15   \n",
       "2        NaN    NaN    NaN        NaN        NaN        NaN    NaN     15   \n",
       "3        NaN    NaN    NaN        NaN        NaN        NaN    NaN     15   \n",
       "4        NaN    NaN    NaN        NaN        NaN        NaN    NaN     15   \n",
       "\n",
       "   EVDI2  EVDIT  EVOII  EVDOA  EVDOV  EVDSE  EVACS   EVPSS  EVMSC  EVRER  \\\n",
       "0     14     14      0     27   13.9      0    0.0  46.225   52.9      0   \n",
       "1     14     14      0     27   13.9      0    0.0  46.225   52.9      0   \n",
       "2     14     14      0     27   13.9      0    0.0  46.225   52.9      0   \n",
       "3     14     14      0     27   13.9      0    0.0  46.225   52.9      0   \n",
       "4     14     14      0     27   13.9      0    0.0  46.225   52.9      0   \n",
       "\n",
       "   EVDRV  EVMTR  EVODO  EVOAS  EVHTR  EVACE  EVTRE  EVCLC  EVBFN  EVIST  \\\n",
       "0 -65532      0   2572   13.0      0   13.7   50.0     55      0      0   \n",
       "1 -65532      0   2572   13.0      0   13.7   50.0     55      0      0   \n",
       "2 -65532      0   2572   13.0      0   13.7   50.0     55      0      0   \n",
       "3 -65532      0   2572   13.0      0   13.7   50.0     55      0      0   \n",
       "4 -65532      0   2572   13.0      0   13.7   50.0     55      0      0   \n",
       "\n",
       "   EVHTP_AVG  EVHTP_Max  EVHTP_Min  EVVBT  EVGSM  EVACO_X  EVACO_Y  EVACO_Z  \\\n",
       "0          0          0          0    137      0     -820      654       23   \n",
       "1          0          0          0    137      0     -820      654       23   \n",
       "2          0          0          0    137      0     -820      654       23   \n",
       "3          0          0          0    137      0     -820      654       23   \n",
       "4          0          0          0    137      0     -820      654       23   \n",
       "\n",
       "   Unnamed: 164  elapsed_tm  \n",
       "0           NaN           0  \n",
       "1           NaN         100  \n",
       "2           NaN         200  \n",
       "3           NaN         300  \n",
       "4           NaN         400  "
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9GvnZLqVlXjY7GgAAZQ4FDSWqQbWKmjGwhZ7r2EA7j2dpwKwkzfn5mPIKOJsGAEBxUdBQ4hwMQ31b1NDimHC1qVtFb284rGFzt2hP+nmzowEAUCZQ0GA1Ph4uer1HkF57oKnOXs5V7PytmvbtQV3KYUkOAAD+CgUNVndfYDUtjglX7+DqWrjlF/WPS9TGQ2fMjgUAgM2ioKFUuLs46l/3B+qjASFyc7boyaW7NPbLZJ26mGN2NAAAbA4FDaUqpGZlzY0O1aNt62hdyin1m5mo5TuPsyQHAAC/Q0ErCr2hxDlZHDT8zjqaPzRMgd4V9crqA3p08Q6lnrHPzXkBAPgjChpMU7eqmz7oF6znOwXqwMmLGjQ7STN+PKLc/AKzowEAYCoKGkxlGIZ6NK+uxbHhurdBNU3/4YgGz9mi7b+cMzsaAACmoaDZGMMwO4E5qlV01qRuTfRmryBdzsnX3xZu1+Q1B3ThSp7Z0QAAKHUUNNiUuwO8tCgmXIPCamrpjuPqOzNRaw+cMjsWAAClioIGm+PmbNFT99bXzEEtVdXNSf/6Yo+eXb5bGeevmB0NAIBSQUGDzWrq56FZg1tqZLt6+jH1rPrHJWrx1l+Vz76eAIByjoIGm+ZocVB0q9paOCxMzap76PW1KXp44TalnLxodjQAAKyGgoYyoZZnBb3Tp7le7tpIxzKzNWTuFr3//WFdyWNJDgBA+UNBK0IhK9XaDMMwFNnEV0tiwtWliY8++emYBs1OUuLRTLOjAQBQoihoKHM83Zw0oUsjvftgcxUUFmrEkh16+at9yryca3Y0AABKBAUNZdYddapowdAwDbujtlbuyVC/mYn6OvkE+3oCAMo8ChrKNFcnix6/p57mRIeqRmVXPb9yr/75+S79ei7b7GgAANwyChrKhUBvd308sIWeua++tv+Spf5xiZqbmKY8luQAAJRBFDQbY8hO93oqARYHQ/1Da2pRTJha+XvqrfWHFDtvq/ZmnDc7GgAAN4WChnLHr5Kr3ugZpMndm+jkxRwNm7dV/1l3SJdz882OBgBAsVDQUC4ZhqGODb21JCZcPZtX17ykNPWPS9QPh8+YHQ0AgCJR0FCuebg6akxEoD7sHyIXRwf98/Ndej4+WWcu5ZgdDQCAG6KgFYFbzMuHlrUqa150mB5pU0drD5xS35mJ+mJXOktyAABsEgUNdsPZ0UEP31VH86LDFODlpolf79djS3bo6NnLZkcDAOAaFDTYnXpebpreP0RjIgK198QFDZyVqJk/HVVuPvt6AgBsAwUNdsnBMNQ7uLqWxISrXX0vvfd9qqLnbtHOX7PMjgYAAAUN9q2au4te7d5Ub/QM0vnsPA1fsE2vJ6TowpU8s6MBAOwYBQ2Q1K6+lxbHhqtfyxpasu1X9Y9L1PqUU2bHAgDYKQqajWEfAfNUdHbUMx0aaOagFqpcwUnPLN+jxxds1ckLV8yOBgCwMxQ04A+CqlfS7MEt9fg99bRu/0n1nZmoz7b/qgKW5AAAlBIKGnAdjhYHDbujtuIfb6umfh6avCZFjyzcrkOnL5odDQBgByhoReCkiX2r41VR7z7YXBO6NFLqmUsaPHuLpm9M1ZU8luQAAFgPBQ0ogmEYigry1ZLYcHVq7K0Zm45q8OwkbUnLNDsaAKCcoqABxVTFzVkvRTbWO32aKbegUH9ftEOvrN6vrOxcs6MBAMoZChpwk+6sW1WLhoVpaKta+nJXuvrOTNQ3+06yrycAoMRQ0IBb4Opk0RPtAjRrSKh8PVw09stkjVq2W+lZ2WZHAwCUAxQ04DY08nHXzEEt9dS9AUo6lql+cYlasOUX5RdwNg0AcOsoaMBtsjgYGhRWS4tiwhVay1PTvj2o2Plbte/EBbOjAQDKKAqajTHYSqDMql7JVW/2CtKkbk2Ucf6Khs3donc2HFJ2br7Z0QAAZQwFDShBhmEoopG3lsSGq1szP83+OU0DZiXpp9SzZkcDAJQhFLQicCcRbkUlVyc936mhPugXLIuDocc/26nxq/bq7KUcs6MBAMoAChpgRWG1PTV/aJiG3+mv1Xt/29czfncGS3IAAP4SBQ2wMhdHBz3atq7mRoeqTlU3Tfhqnx7/dKfSMi+bHQ0AYKMoaEApqV+toj4aEKLR9zfQ7vTzGjArSbM2H1NePvt6AgCuRUEDSpGDYahPSA0tjgnXXfWq6r/fHdbQeVu1+3iW2dEAADaEggaYwMfDRa890FSvP9BU5y7nKnb+Nr3x7UFdzMkzOxoAwAZQ0AAT3RtYTYtiwvVgixpatOUX9Y9L0ncHT5sdCwBgMgoaYDJ3F0c917GBZgxsoYrOFo1atltjVuzRqQtXzI4GADAJBQ2wEcE1KmludKhGtK2rDQdPq29copbuOK4CluQAALtj1YJ2/PhxRUdHKzIyUlFRUZo1a5YkacqUKerSpYu6d++uf/zjH8rK+v83SE+fPl0RERHq3LmzvvvuO2vGKx7+cUQpcrI46KE7/TV/aJga+bhr0jcH9Oii7Uo9fcnsaACAUmTVgmaxWDR69GitWrVKixYt0vz585WSkqK2bdvqyy+/1IoVK1S3bl1Nnz5dkpSSkqL4+HjFx8drxowZeumll5Sfzz6GsD91qrrp/b7BeqFzQx08fUmD5iTpox+OKCePJTkAwB5YtaD5+PgoKChIkuTu7q6AgABlZGTo7rvvlqOjoySpRYsWSk9PlyQlJCQoKipKzs7Oql27turUqaMdO3ZYMyJgswzD0APN/LQkNlwdAqvpwx+PaMicLdqWds7saAAAK3MsrS+Ulpam5ORkhYSEXHP8s88+U2RkpCQpIyPjmo/7+voqIyPjL9/XYjHk6elW8oH/x/1C6e6d6ObmYtV5boXF4mBzmUqLLczu6emm/w4O0/r9JzV+xW49vGi7BrSqrWcjGqpSBSerfm1bmN9M9jy/Pc8u2ff89jy7p6ebzcxfKgXt4sWLGjlypMaOHSt3d/erx99//31ZLBY98MADknTd/QkNw/jL987PL1RmpvXuz7lwPttq7309ly5dseo8t8LT083mMpUWW5o9xKeiFgwN0/SNR7Qg8Zi+2ZOhZzvUV4fAakX+OblVtjS/Gex5fnueXbLv+e159szMS1af39vbo1ivs/pTnLm5uRo5cqS6d++uTp06XT2+dOlSrVu3TlOnTr36j4ufn9/Vy53Sb2fUfHx8rB0RKDMqOFn05L0BihvcUtUqOmv0imQ9s3yP0rNK9wcJAIB1WbWgFRYWaty4cQoICFBsbOzV4xs2bNBHH32k999/XxUqVLh6vEOHDoqPj1dOTo6OHTum1NRUBQcHWzMiUCY18fVQ3OCW+mf7AG0+clb945K0aMsvyi/gqWMAKA+seokzKSlJy5cvV8OGDdWjRw9J0qhRo/TKK68oJyfnamkLCQnRyy+/rMDAQEVGRqpr166yWCx68cUXZbFYrBkRKLMcHQwNCa+l+wK9NHlNiqZ+e1Crkk9oXKdABXq7F/0GAACbZdWCFh4ern379v3pePv27W/4OSNGjNCIESOsGQsoV2pWrqC3ezfT13tPatq3BxU9d6uiw2tp+J3+cnXiBxwAKIvYSaAIXDBCWWAYhro08dHi2HB1beKjuM3HNHB2kjYfOWt2NADALaCgAeWIZwUnvdilkd7r21yGpH98ulMTvtqnzMu5ZkcDANwEChpQDrXyr6L5Q8MU27q2vko+ob4zE7UqOeO6S9kAAGwPBQ0op1ydLHrs7nqaOyRUtTxd9eLKfRr52S6lZV42OxoAoAgUNKCca+BdUTMGtNCzHRpo5/EsDZiVpDk/H1MeS3IAgM2ioAF2wOJgqF/LGloUE67Wdaro7Q2HNWzuFu1JP292NADAdVDQADvi6+GiqT2aasoDTXXmUq5i52/Vm+sO6lJOvtnRAAC/Q0ED7IxhGOoQWE1LYsPVK7i65if9ogGzErXx0BmzowEA/oeCBtgpdxdHjb4/UDMGhMjV0aInl+7SuC+TdfpijtnRAMDuUdCKwKoEKO9CalbW3OhQ/f2uOvo25ZT6zkzU8p3HWZIDAExEQbMxhmGYHQF2yNnRQX9rU0fzh4apgXdFvbL6gB5dvEOHT100OxoA2CUKGoCr6lZ10wf9gjUuIlAHTl5Ut3c36uNNR5SbX2B2NACwKxQ0ANdwMAz1DK6uxbHhimjsow82HtGQOVu049css6MBgN2goAG4rmoVnfWf/i30Zq8gXcrJ198WbNOUNQd04Uqe2dEAoNyjoAH4S3cHeGlRTLgGhNbU5zuOq19cotYdOGV2LAAo1yhoAIrk5mzRqPvq65NBLeVZwUnPfrFHzy7frRPnr5gdDQDKJQoagGIL8vPQ7MEtNbJdPf2Yelb94hK1ZNuvKmBJDgAoURQ0ADfF0eKg6Fa1tXBYmJpV99BrCSn624LtOsiSHABQYihoReC8AHB9tTwr6J0+zfVSZCMdy7ysIXO26P2NqbqSx5IcAHC7KGgAbplhGOra1FdLYsLVubG3Ptl0VINmJynpWKbZ0QCgTKOg2Rj2EUBZ5OnmpAmRjfXfB5srv6BQjy7eoVe+3q9zl3PNjgYAZRIFDUCJaV2nihYOC9OwO2rry93p6heXqNV7T7CvJwDcJAoagBLl6mTR4/fU0+whofKr5Kpx8Xv15NJd+vVcttnRAKDMoKABsIqGPu76ZGALPX1ffW1NO6f+cYman5SmvALOpgFAUShoAKzG4mBoQGhNLY4JV7i/p95cd0gPzd+qfRkXzI4GADaNggbA6vwquWpazyC92q2JMs5f0bB5W/TW+kO6nJtvdjQAsEkUNAClwjAM3d/IW0tiw9W9mZ/mJqZpwKwk/Zh6xuxoAGBzKGhF4OkzoGRVcnXSuE4NNb1/sJwcDI38bJdeWLlXZy7lmB0NAGwGBQ2AKUJreWr+0DA93MZfa/adVL+ZiVqxK50figBAFDQAJnJ2dNAjd9XVvKGhqlvVTS9/vV+PfbpTx85eNjsaAJiKgmZjDLYSgB0K8KqoDweEaMz9DZScfl4DZydp5k9HlZfPvp4A7BMFDYBNcDAM9Q6poSWx4bo7oKre+z5V0XO3atfxLLOjAUCpo6ABsCne7i6a3L2ppvYIUlZ2rh6av01T16boYk6e2dEAoNRQ0ADYpPYNvLQoJlz9WtbQ4q2/qt/MRK1POW12LAAoFRQ0ADbL3cVRz3RooE8GtVAlVyc9s3y3/vXFHp26cMXsaABgVRQ0ADavWfVKmjOkpR67u66+P3RafeMS9fn2X1XAkhwAyikKGoAywdHioNjW/lowLFyNfT306poUPbJwuw6dvmh2NAAocRQ0AGWKf5UKeu/B5hrfpaFSz1zS4NlbNH1jqnLyWJIDQPlBQQNQ5hiGoW5BflocG677G3lrxqajGjQ7SVvSMs2OBgAlgoIGoMyq6uasiV0b6+0+zZSbX6C/L9qhf6/er6zsXLOjAcBtoaABKPPa1K2qhTHhig6vpRW70tV3ZqK+2XeSfT0BlFkUNBvDTk/ArangZNHI9gGaNThUvh4uGvtlskYt2630rGyzowHATaOgAShXGvm665NBLfXUvQFKPJqpfnGJWrDlF+UXcDYNQNlBQQNQ7jg6GBoUVkuLYsLVslZlTfv2oB5asE37T1wwOxoAFAsFDUC5VaOyq/7Tq5n+HdVY6VnZGjp3i97ZcFjZuflmRwOAv0RBA1CuGYahTo19tDgmXN2C/DT752MaMCtJP6WeNTsaANwQBa0IPAQGlA+VKzjp+c4N9UG/YFkcDD3+2U6NX7VXmZdYkgOA7aGgAbArYbU9NX9omB66019f7z2pB2f+rJV7MliSA4BNoaABsDsujg4a0bau5kaHyr+Km8av2qfHP92ptMzLZkcDAEkUNAB2rEG1ipoxMET/6thAu9PPa8CsJM3efEx5+ezrCcBcFDQAds3BMPRgixpaHBOuNnWr6J3vDmvovK3anX7e7GgA7BgFzdYY7CUAmMHHw0Wv9wjSaw80VeblXD00f6teWZmsizl5ZkcDYIcoaADwO/cFVtPimHD1Dq6u2ZuOqH9ckr4/dNrsWADsjFUL2vHjxxUdHa3IyEhFRUVp1qxZkqTMzEzFxsaqU6dOio2N1blz5yRJhYWFeuWVVxSK8lFLAAAgAElEQVQREaHu3btr9+7d1owHANfl7uKof90fqIV/a62KzhY9tXS3xqxI1qmLOWZHA2AnrFrQLBaLRo8erVWrVmnRokWaP3++UlJS9OGHH6pNmzZavXq12rRpow8//FCStGHDBqWmpmr16tWaOHGiJkyYYM14APCXQv2raG50qEa0rasNB0+p38xELd1xXAUsyQHAyqxa0Hx8fBQUFCRJcnd3V0BAgDIyMpSQkKCePXtKknr27Kk1a9ZI0tXjhmGoRYsWysrK0okTJ6wZsUj8NQzYNyeLgx6601/zh4apoU9FTfrmgB5dvEOppy+ZHQ1AOeZYWl8oLS1NycnJCgkJ0enTp+Xj4yPptxJ35swZSVJGRob8/Pyufo6fn58yMjKuvvZ6LBZDnp5uVsvtnplttfe+nopuzlad51ZYLA42l6m02PPsEvP/fn5PTzcteNhLn275RVO+3qdBc5I0on19PXJPgFwcy9/tvHzv7Xd+e57d09PNZuYvlYJ28eJFjRw5UmPHjpW7u/sNX3e9lbyNIp5qzM8vVGam9X6SvXDhitXe+3ouXsqx6jy3wtPTzeYylRZ7nl1i/uvNH1G/qkKHhenNdQf19toUrdj2q8ZGBKpFrcompbQOvvf2O789z56Zecnq83t7exTrdVb/sS83N1cjR45U9+7d1alTJ0mSl5fX1UuXJ06cUNWqVSX9dsYsPT396uemp6f/5dkzADCDV0VnvRLVRP/p3UzZefl6eNF2TV5zQBeusCQHgJJh1YJWWFiocePGKSAgQLGxsVePd+jQQcuWLZMkLVu2TB07drzmeGFhobZt2yYPDw8KGgCb1bZeVS0cFq5BYTW1dMdx9Z2ZqLUHTrGvJ4DbVmRB27Fjxw0/9n8l60aSkpK0fPlybdq0ST169FCPHj20fv16PfLII9q4caM6deqkjRs36pFHHpEktW/fXrVr11ZERIReeOEFjR8//ibHAYDS5eZs0VP31lfc4Jbyquisf32xR88u36OM86V7ewSA8qXIe9DGjRun0NBQPf3006pUqZIkaf/+/XrppZdUuXLlq09jXk94eLj27dt33Y/935pov2cYht2XMvYRAMqmJr4eihvcUguS0jT9hyPqH5eox+6uqz4hNWRx4E82gJtTZEFbunSpPv74Y/Xs2VOPPfaY9u/fr/Xr12v06NG67777SiMjAJQJjg6GolvVVoeG1TR5TYpeX3tQXyWf0NiIhmrgXdHseADKkCILmqOjo/7+97/LYrHo+eefl4+Pj5YsWSJfX9/SyAcAZU7NyhX0du9m+nrvSU379qCGzN2ioa1q6aHW/nJ1spgdD0AZUOQ9aEePHtXw4cP1008/aeXKlXrooYc0ZMgQffbZZ6WRz3SFLFUL4BYYhqEuTXy0ODZckU18NPOnYxo0O0k/Hz1rdjQAZUCRBW348OHq27evPvroIwUEBCgmJkZz587V999/rwEDBpRGRgAoszwrOGl8l0Z698HmKpT02JKdevmrfcq8nGt2NAA2rMhLnMuWLVPFitfeO+Hr66s333xTP/zwg9WCAUB5ckedKlowNEwfbzqqOYlp+v7QGY26r746N/YuckFuAPanyDNofyxn0m+XPd977z1NmjTJKqEAoDxydbLoH/fU05whLVWjsqteWLlXIz/fpV/OXTY7GgAbU+yFak+cOKG4uDg9+OCDioqKUkFBgd544w1rZgOAcinQ210fD2yhZ+6rrx2/ZGlAXJLmJqYpr4B7XgH8psiCtnjxYg0dOlTR0dE6e/asXnnlFXl7e+vxxx9Xo0aNSiMjAJQ7FgdD/UNralFMmFr5e+qt9YcUM2+rkjPOmx0NgA0osqC9/PLLKigo0NSpU/XUU0+pcePG3C8BACXEr5Kr3ugZpCndm+jUxRzFzNuqN9cd1OXcfLOjATBRkQ8JbNiwQV999ZUmT56sU6dOKTIyUnl5bAhsLVRfwP4YhqEODb3Vyr+K/vvdYc1P+kXfHjilf90fqLb1qpodD4AJijyDVrVqVQ0aNEjz5s3TrFmz5OHhIS8vL0VGRmratGmlkREA7IKHq6PGRATqo/4hcnW06MnPd+n5+GSdvphjdjQApazYDwlIkp+fn4YPH67PP/9c7733npydna2Vy2YUcs8ugFLWolZlzY0O1SN31dHaA6fULy5RX+xMVyF/IQF2o8hLnKtXr77hxxo2bFiiYQAAv3F2dNDDbero/obeevWb/Zq4er9WJmdozP2BqlPVzex4AKysyII2cuRINWnSRI0bN77uxzt16lTioQAAv6nn5aYP+odo+c50vb3hkAbNTtLwO+soulUtOVlu6iIIgDKkyIL2zjvvaOXKldq3b586duyobt26qU6dOqWRDQAgycEw1Cu4uu4JqKo3vj2k9zemavW+Exob0VDBNSqZHQ+AFRT541dERITefPNNzZ07V/7+/po8ebIGDhyozZs3l0Y+u8MdJgBupJq7i17t3kRv9AzShSv5+tuCbXotIUUXrvBkPVDeFPv8uIuLizw8POTu7q7Lly/rypUr1swFALiBdvW9tCgmTP1Da+rTbb+qf1yi1h04ZXYsACWoyEucmzZtUnx8vHbs2KG77rpLQ4cOVfPmzUsjGwDgBio6O+rp++qrS2Nv/fubA3r2iz26t4GXnu3QQD4eLmbHA3CbiixoMTExatSokcLCwpSTk6Ply5dr+fLlVz/+/PPPWzUgAODGgqpX0uzBLTUv6Rd99OMR9YtL1OP31FPvkOpyYNcXoMwqsqC9+uqrpZED/8NfpwBulqPFQcPuqK2ODavp1W8OaEpCilYln9DYiEDVr1bR7HgAbkGRBa1Xr17FeqOJEyfqhRdeuO1AAIBbU8uzgv77YHOtSj6had8e1JA5WzT0jtp6qLW/XBxZkgMoS0rsT+yWLVtK6q0AALfIMAx1beqrJbHh6tTYW59sOqpBs5OUdCzT7GgAbgI/UgFAOVTFzVkvRTbWf/s0V35BoR5dvEOvfL1f5y7nmh0NQDFQ0ACgHGtdt4oWDgvT0Fa19eXudPWLS9TqvSfY1xOwcSVW0PjDDgC2ydXJoifa1dOsIaHy9XDRuPi9emrpbh3PyjY7GoAbKLKgffXVV8ValHbo0KElEggAYB2NfNw1c1BLjbqvvrakZarfzETNT0pTXgE/YAO2psiCtmLFCt1777167rnntH79euXn51/3db179y7xcACAkmVxMDQwtKYWx4Qr3N9Tb647pIfmb9W+jAtmRwPwO0UWtHfffVfffPON2rRpozlz5qh9+/YaP368fv7559LIBwCwAr9KrprWM0iTujVRxvkrGjZvi95ef0jZudf/IRxA6SpyHTRJcnd3V69evdSrVy+dPXtWX3/9tSZOnKhz585p/fr11s4IALACwzAU0chbret46p0NhzUnMU0JB05pzP0N1KWFm9nxALt2Uw8JnDt3Tt98841Wrlypc+fOqVOnTtbKZTNK+9kHdmYBUNoquTppXKeGmt4/WE4Ohp74bJee+XSHzl7KMTsaYLeKPIN24cIFrVmzRvHx8dqzZ486dOigESNG6M4775RBmwCAciO0lqfmDQ1T3E9HNevnY1q374SevDdAUU19+fseKGVFFrSOHTvq7rvv1sCBA3XPPffIycmpNHIBAEzg4uigv7etq96t/DXmsx166av9it9zQmPvD1TtKhXMjgfYjSIL2rp161ShQgVduXJFhw8flmEY8vf3l4uLS2nkAwCYINDHXR8OCNHSHcf1zobDGjg7SX+7019DwmvJ0cIa54C1FVnQnJyc9Prrr+vTTz9VzZo1VVBQoPT0dPXu3VtPPfUUZ9QAoJxyMAz1CamhdvW9NHXtQb37faq+3ntS4zoFqln1SmbHA8q1In8Meu2115SZmamEhAR9/vnnWrZsmdasWaPz589rypQppZERAGAib3cXTXmgqab2aKqs7Fw9NH+bpq5N0cWcPLOjAeVWsS5xfv3119fcIOru7q4JEyYoMjLSquEAALajfYNqCqvtqfe/T9Xirb/q2wOn9K/7A9WuvpfZ0YByp8gzaIZhXPfpHYvFwlM9AGBn3F0c9WzHBvp4YAt5uDrq6WW7NXrFHp26UPSWgACKr8iCVr9+fS1btuxPx5cvX6569epZJRQAwLY1r1FJc4eE6rG76+q7g6fVNy5Rn2//VQWlvXgkUE4VeYlz/Pjxevzxx/XZZ58pKChIhmFo586dys7O1rvvvlsaGU1VKP6yAYDrcbQ4KLa1vzo29Naraw7o1TUpWpV8QmMjGqqeFzsRALejyILm6+urJUuW6Mcff1RKSooKCwvVrl07tWnTpjTy2SEuGwMoW/yrVNB7DzbXl7sz9Nb6Qxo0O0mxrWsr5g5/OTuyJAdwK4q1F6cktWnTRm3atNHly5eVkpKiM2fOqGrVqtbMBgAoIwzDUPdmfmobUFVvrjukj348qm/2ndTYiIZqWauy2fGAMqfIH20SEhLUoUMH9erVS+vXr1dUVJQmTpyo7t27a+nSpaWREQBQRlR1c9bEro31Vu9myskr0COLtmvSN/t1PpslOYCbUeQZtLfeeksff/yxzp8/r2HDhumLL75Q7dq1dfr0acXExKhXr16lkRMAUIbcVa+qFsaEa/rGI1qwJU0bDp7RM/fVV8eG1VgBACiGIs+gOTg4qF69egoODlatWrVUu3ZtSZKXl5csFovVAwIAyqYKThY9eW+AZg1uKe+KzhrzZbKeXrZb6VnZZkcDbF6RBa2goEDnzp3T2bNnZRiGzp07p8zMTGVmZqqgoKA0MgIAyrDGvh6aObilnmwfoJ+PZqp/XJIWbvlF+QU8JQ/cSJGXOC9cuKDevXur8H9r2/z+kianqQEAxeHoYGhweC3dG+ilKWtS9Ma3B/VV8gmN6xSoQG93s+MBNqfIgrZ27drSyAEAsAM1K1fQW72bafXek3rj24OKnrtVQ8Jr6W93+svVidtmgP9T5CXOrl276oMPPtCxY8dKI4/NYVFsAChZhmGocxMfLYkNV1RTH83afEwDZyfppyNnzY4G2IwiC9q0adN08eJFxcbGqm/fvoqLi1NGRkZpZAMAlGOVKzjphc6N9H7fYBmSHv90pyZ8tU+Zl3LNjgaYrshLnI0bN1bjxo319NNPa9u2bVq5cqX69+8vf39/devWTf369SuNnACAcirc31Pzh4Zp5k9HNevnNG08dEZP3RugyCY+3OsMu3VTe3C0aNFCY8eO1ZQpU5SVlaWXX37ZWrnsFn8XAbBHrk4Wjbi7nuZGh6q2p6vGr9qnkZ/tUlrmZbOjAaYo9lZPO3bsUHx8vFavXq2aNWuqX79+6tKlizWzAQDsTINqFfXRgBb6bPtxvff9YQ2YlaS/31VHA8NqydGBn2BhP4osaNOmTdPKlStVqVIlRUVFacGCBfLz8yuNbAAAO2RxMNSvZQ21b+Cl1xNS9PaGw/9bkqOhmvp5mB0PKBVFFjRnZ2d99NFHqlev3k2/+ZgxY7Ru3Tp5eXnpyy+/lCQlJydr/PjxunLliiwWiyZMmKDg4GAVFhbq3//+t9avXy9XV1dNnjxZQUFBNz8RAKBc8PVw0dSeQfr2wCm9lpCi2Plb1b9lTT3atq7cnFmSA+Vbkfegubi4XC1nq1atuuZj06ZN+8vP7d27t2bMmHHNsddff13/+Mc/tHz5cv3zn//U66+/LknasGGDUlNTtXr1ak2cOFETJky4mTkAAOXUfYHVtCQ2XL2Cq2vBll/UPy5RGw+dMTsWYFVFFrSVK1de/fWHH354zce+++67v/zcVq1aqXLlytccMwxDFy9elCSdP39ePj4+kqSEhAT17NlThmGoRYsWysrK0okTJ4o3BQCgXHN3cdTo+wM1Y0CIKjhb9OTSXRr7ZbJOXcwxOxpgFUVe4iz83UqthX9YtfWPvy+OsWPHavjw4ZoyZYoKCgq0cOFCSVJGRsY197b5+fkpIyPjaoG7EYvFkKen203nKK6Kpy9Z7b2v+/Uqulh1nlthsTjYXKbSYs+zS8xvz/Pb6uztPd3UppGvPvr+sN5dl6KfjpzV6C6N9WBozRJdksNW5y8N9jy7p6ebzcxfZEH7/f/wf/yf/1b+MCxYsEBjxoxR586dtXLlSo0bN05xcXHXLXvFef/8/EJlZlqvRF24cMVq7309Fy9eseo8t8LT083mMpUWe55dYn57nt/WZx/corra+lfWpG8OaOyyXfo08ZjGRASqbtWS+YfV1ue3JnuePTPzktXn9/Yu3oMuRRa0vXv3KjQ0VIWFhbpy5YpCQ0Ml/Xb2LCfn5k8tL126VOPGjZMkRUZG6vnnn5f02xmz9PT0q69LT08v8uwZAMB+1a3qpg/6BWvFrnS9tf6wBs1O0kOt/TXsjtpystzUMp+AzSmyoCUnJ5foF/Tx8dHmzZvVunVrbdq0SXXr1pUkdejQQXPnzlVUVJS2b98uDw8PChoA4C85GIZ6NK+utgFemvbtQU3/4YhW7zupcRGBCqlZueg3AGxUsReqvRWjRo3S5s2bdfbsWbVr105PPPGEJk6cqEmTJikvL08uLi5XdyNo37691q9fr4iICFWoUEGTJk2yZjSbxTKMAHDzqlV01qRuTdS1qY+mrEnR3xZuV5+Q6nr8nnpyd7HqP3WAVVj1/9obLcPx+eef/+mYYRgaP368NeMAAMq5uwO8FBrjqek/pGrhll+0PuW0nu3YQB0Cq5kdDbgpXKQHAJQrbs4WPXVvfc0c1FJV3Zz0ry/26Nnlu5VxvnQf+gJuBwUNAFAuNfXz0KzBLTWyXT39mHpW/eMStXjrr8ovuPklooDSRkEDAJRbjhYHRbeqrYXDwtSsuodeX5uihxduU8rJi2ZHA/4SBa0o/KAFAGVeLc8KeqdPc73ctZGOZWZryNwtev/7w7qSV2B2NOC6KGgAALtgGIYim/hqSUy4ujTx0Sc/HdOg2UlKPJppdjRYmZOl7K2RQEEDANgVTzcnTejSSO8+2FwFhYUasWSHXv5qnzIv55odDVbS1Ld4q/fbEgoaAMAu3VGnihYMDdOwO2pr5Z4M9ZuZqK+TT9zSPtNASaOgAQDslquTRY/fU09zokNVo7Krnl+5V//8fJfSztrnXpSwHRQ0EzX0rvinY7ew/zwA4DYFervr44Et9Mx99bX9lyx1fWej5iamKY8lOWASChoAAJIsDob6h9bUopgwtQmoqrfWH1LsvK3am3He7GiwQxQ0AAB+x6+Sqz4YHKrJ3Zvo5MUcDZu3Vf9Zd0iXc/PNjgY7QkEDAOAPDMNQx4beWhITrp7Nq2teUpr6xyXqh8NnzI4GO0FBK8KVfBYxBAB75eHqqDERgfqwf4hcHB30z8936fn4ZJ25lGN2NNyEsnh/NwWtCKG1Kt/W5zerXvbWXgEAXKtlrcqaFx2mR9rU0doDp9R3ZqK+2JXOkhywGgpaEdxdHG/r8+/w9yyhJAAAMzk7Oujhu+poXnSYArzcNPHr/XpsyQ4dPXvZ7GgohyhoJuLnLgAoe+p5uWl6/xCNiQjU3hMXNHBWomb+dFS53BKDEkRBAwDgJjkYhnoHV9eSmHC1q++l975PVfTcLdr5a5bZ0VBOUNAAALhF1dxd9Gr3pnqjZ5DOZ+dp+IJtei0hRReu5JkdDWUcBc3GGCqDj5oAgJ1rV99Li2PD1a9lDX267Vf1j0vU+pRTZsdCGUZBAwCgBFR0dtQzHRrok0EtVMnVSc8s36PnvtijkxeumB3NrrWuUzYf1qOgAQBQgppVr6Q5Q1rqH3fX1Q+Hz6jvzER9uu1XFbAkhyme6dDA7Ai3hIIGAEAJc7Q4KKa1vxYMDVNTPw9NSUjRwwu36+Cpi2ZHQxlBQQMAwEpqV6mgdx9srvFdGurImUsaMmeLPtiYqit5LMmBv0ZBAwDAigzDULcgPy2JDVdEI299vOmoBs9OUtKxTLOjwYZR0AAAKAVV3Jz1ctfGeqdPM+UWFOrRxTv0yur9ysrONTtauVZW10agoAEAUIrurFtVC4eFKTq8lr7cla6+MxO1eu8J9vXENShoAACUsgpOFo1sH6BZg0Pl6+GicfF7NWrZbqVnZZsdDTaCggYAgEka+brrk0Et9dS9AUo6lql+cYlasOUX5RdwNs3eUdBsTVm9WA4AuCWODoYGhdXSophwtaxVWdO+PajY+Vu178QFs6PBRBQ0AABsQPVKrvpPr2b6d1RjZZy/omFzt+idDYeUnZtvdjSYgIJmZZykBgAUl2EY6tTYR4tjwtWtmZ9m/5ymAbOS9FPqWbOjoZRR0AAAsDGVKzjp+U4N9UG/YFkcDD3+2U6NX7VXZy/lmB0NpYSCBgCAjQqr7an5Q8M0/E5/rd57Un1nJip+dwZLctgBChoAADbMxdFBj7atq7nRoapT1U0Tvtqnxz/dqbTMy2ZHgxVR0AAAKAPqV6uojwaE6F8dG2h3+nkNmJWkWZuPKS+ffT1vhrOlbCyXQEEDAKCMcDAMPdiihhbHhOuuelX13+8Oa+i8rdp9PMvsaGXCw238Ff/InWbHKBYKGgAAZYyPh4tee6CpXn+gqc5dzlXs/G1649uDupiTZ3Y0m9bKv4o83ZzMjlEsFDQT1a3q9qdjlV0dTUgCACiL7g2spkUx4XqwRQ0t2vKL+scl6buDp82OZVMMo2xc0vwjCppJ/tunuV7o3PBPx5tVr2RCGgBAWeXu4qjnOjbQjIEtVNHZolHLdmvMij06deGK2dFwGyhoJahlzeKXq/reFVXByXLNsRY38fkAAPxecI1KmhsdqhFt62rDwdPqG5eopTuOq4AlOcokCpoN8arobHYEAEAZ5mRx0EN3+mv+0DA18nHXpG8O6NFF25V6+pLZ0XCTKGilKKx25Rt+bHyXhnq+058veQIAcLPqVHXT+32D9ULnhjp4+pIGzUnSRz8cUU4eS3KUFRS0UtS+QbUbfqxbkJ/cXXhAAABQMgzD0APN/LQkNlwdAqvpwx+PaMicLdqWds7saCgGClpJKqNPigAAyq+qbs56JaqJ/tO7mbLz8vXwou169ZsDOp/Nkhy2jIIGAIAdaFuvqhbFhGtwWC0t23lcfeMSlbD/JPt62igKGgAAdqKCk0VP3huguMEtVa2is0avSNYzy/coPSvb7Gj4Awqald3oBxMuhgIAzNLE10Nxg1vqn+0DtPnIWfWPS9KiLb8ov4CzabaCggYAgB1ydDA0JLyWFsaEKbhmJU399qCGL9imvennzY4GUdBuS/1qf96qCQCAsqRm5Qp6u3czTezaWL+ey1av93/Qu98dVnZuvtnR7BoF7Tb88fIlly0BAGWRYRjq0sRHi2PD1aNFDcVtPqaBs5O0+chZs6PZLQpaKeraxMfsCAAA3JBnBSdN7tVc7/VtLkPSPz7dqQlf7VPm5Vyzo92SNnWrqEZlV7Nj3BIKWimqXMFJVd2czI4BAMBfauVfRfOHhim2dW19lXxCfWcmalVyRplbkuPtPs3l6FA2r29R0AAAwJ+4Oln02N31NHdIqGp5uurFlfs08rNdSsu8bHY0u2DVgjZmzBi1adNG3bp1u+b4nDlz1LlzZ0VFRem11167enz69OmKiIhQ586d9d1331kz2k2Z1LOZ2REAADBFA++KmjGghZ7t0EA7j2dpwKwkzfn5mPJYksOqrFrQevfurRkzZlxzbNOmTUpISNCKFSsUHx+v4cOHS5JSUlIUHx+v+Ph4zZgxQy+99JLy823jCZK+YbXMjgAAgGksDob6tayhRTHhal2nit7ecFjD5m7RHpbksBqrFrRWrVqpcuXK1xxbsGCBHnnkETk7O0uSvLy8JEkJCQmKioqSs7OzateurTp16mjHjh3WjAcAAG6Cr4eLpvZoqikPNNWZS7mKnb9Vb647qEs5tnFCpTxxLO0vmJqaqsTERL355ptycXHRc889p+DgYGVkZCgkJOTq63x9fZWRkVHk+1kshjw9rbsemcVy/R7r4HDtcUfHP7/O1fX/PxTg6emmJzo00EtfJquWbyW5/O711p7hdlgsDjadz5rseXaJ+e15fnueXbLv+Ysze+9WFRXRvLqmfrNf8zcf0/qDpzWhe5DubehdSimL5//mcHS0SJLc3V3+cjZPTzeb+d6XekHLz89XVlaWFi9erJ07d+rJJ59UQkLCdZ8MMYyin7zIzy9UZuYla0S96kbfqPyCgmt+n5dX8KfXZGf//0eTMzMvqVsjb3Vr5K3LF7L1+9ssrT3D7fD0dLPpfNZkz7NLzG/P89vz7JJ9z38zsz91Tz11CKiqf68+oIfnJKlTI2+Nuq++vCo6Wzll8fzfHHl5v53hu3Dhyl/Olpl5yerfe29vj2K9rtSf4vT19VVERIQMw1BwcLAcHBx09uxZ+fn5KT09/errMjIy5OPDumEAANiykJqVNTc6VI/cVUffppxS35mJWr7zeJlbksPWlHpBu//++7Vp0yZJ0uHDh5Wbm6sqVaqoQ4cOio+PV05Ojo4dO6bU1FQFBweXdjwAAHCTnB0d9HCbOpofHaYG1dz0yuoDenTxDh05Y59nIUuCVS9xjho1Sps3b9bZs2fVrl07PfHEE+rTp4/Gjh2rbt26ycnJSZMnT5ZhGAoMDFRkZKS6du0qi8WiF198URaLxZrxSlwxrsgCAFBu1fVy0wf9Q/TFznS9veGwBs1O0kN3+mtoq9pyusH93Lg+qxa0adOmXff41KlTr3t8xIgRGjFihDUjAQAAK3IwDPUMrq6763vpjbUH9cHGI/p670mNiwhUSM3KRb8BJLGTgNVxBR4AYI+qVXTWq92baFrPIF3Kydf/a+/+o6oq8z2Of44HSRAFMZFSx9/ij0yMYYJscInhLwTUULMZm0pnHC2tKK/SLDWnlt1pHJ1xWplmria9k42VmbJa1oXMWpqaqYzVpFaOWoAzgeGPBDk8948abgQICufsh3Per788z344+/s9j/CbFpYAABasSURBVGvzYe9z9vnlhoP67/89orNlFU6X1iwQ0JrYc7fHOl0CAADW+GnP9vrbnT/WbTd00qb8Ak167n29deTfTpdVw9uzhzhdQjUEtCbkktT6Kp/fuQQAAKuFBruVNayn1t4+WBEhLfVfr32kuZs/1KkzZU6XViU02K73vRPQAACATwyIbqPnfzZYs3/aXbuOlWjSc+9r44EvVcktOWogoAEAAJ8JcrfQHT/pog2/iNOA6DZ6Iveopr9wUEf/fc7p0qxCQAMAAD7XOSJET2YO1OLRMTpecl4/X/eBVr77ucpq+VaeQERAAwAAjnC5XBrTv6Neuiteo/p20NrdJ3T78/u078Rpp0tzHAENAAA4KiK0pR4Z3VdPZg6Up9Lo13/L16PbPtHX31y85M9tmhbvowp9j48cNgbvaQQAoMnc2LWdNvwiTs/sOq7/ef+E3v2s+JLzO0eE+Kgy3+MMWhO7KoiXFACAK9WqpVuzk7rr+Z/foOi2rZwuxzGkiSZ2TdtWWjK2n9NlAADQrPWJCtPaKbEaO6BjrdvHDYyu9vjuhB/p10O6+qI0nyCgeUFKTAenSwAAoNlzt3DV+Ts1sVu7ao9nDummaQkENEgyvAkNAABHtXS7nC7BK/iQAAAAaLb+ekec8r8odbqMJkdAAwAAzVa3yFB1iwx1uowmxyXOpuTyz9OsAADAtwhoAAAAliGgNaHazp8ZPkcAAAAuEwENAABYK1DPcxDQAABAQLqlz9VOl1AnAhoAAAhIj6f1d7qEOhHQAAAALENAAwAAzUpESEvd0CXC6TK8ihvVNgKf0AQAwPfenJXodAlexxk0AAAAyxDQAACA37n7xi5Ol9AoBDQAAOB3Zt7c3ekSGoWABgAAYBkCWgNFhQU7XQIAAKjHj9qFqHWw2+kyGo1PcTZQzowE/XXfSS3f/pnTpQAAgDq8fHe80yU0Cc6gAQAAWIaA1oSGdI90ugQAAOAHCGhN6Pa4Tk6XAAAA/AABrQm5XK5aRvm6AQAAcHkIaJeha2Rog+f26xjmxUoAAIA/I6BdhiHdI/XCL+IaNPfpSYO0efpPvFwRAAB+LkAvRHGbjcvU6+rWDZoXGuxWqB/chwUAAPgeZ9AaoXcHLmMCANDcXN3a/pvPcwatERaN6qPJg6/VL1886HQpAACggf56xw06dabc6TIuiYDWCK1auhXbOdzpMgAAwGVoFxqsdqF2n0XjEicAAIBlCGgAAACWIaABAABYhoAGAABgGQIaAACAZQhoAAAAliGgAQAAWIaABgAAYBkCGgAAgGUIaAAAAJYhoHnZz3/c2ekSAABAM0NA8zLbv+sLAADYh4AGAACsZWScLsERXg1o2dnZSkxM1NixY2tse/bZZxUTE6Pi4mJJkjFGjz32mFJSUpSWlqYPP/zQm6UBAABYy6sBbcKECVqzZk2N8YKCAu3cuVPXXntt1diOHTt07NgxvfHGG3r00Uf1yCOPeLM0AAAAa3k1oMXHxys8PLzG+OOPP665c+fK5XJVjeXm5mrcuHFyuVyKjY1VaWmpTp065c3yAAAArBTk6x3m5uYqKipKffv2rTZeVFSk6OjoqsfR0dEqKipSVFTUJZ/P7XYpIiLUK7X+/z5a1LqPH47VV8eltnu7h8aoq/9AEMi9S/QfyP0Hcu9SYPdvW++tW5+tMXa59QUFuSVJYWFX1fmz/xm3pX+fBrRvvvlGTz/9tNauXVtjmzE13wT4/TNsdfF4jE6fPt8k9dUlIiK01n38cKy+Oi613ds9NEZd/QeCQO5dov9A7j+Qe5cCu3/bej93rqzG2OXWV1HhkSSdPVtW58/+Z9zb/Xfo0KZB83wa0I4fP66TJ08qIyNDklRYWKgJEyZo48aNio6OVmFhYdXcwsLCes+eAQAA+COfBrSYmBjt2rWr6nFycrJeeuklRUZGKjk5WevXr1dqaqoOHjyoNm3aENAAAEBA8uqHBLKysnTbbbfp888/V1JSkjZu3Fjn3KFDh6pLly5KSUnRggULtGjRIm+WBgAAmpEh3SOdLsGnvHoGbdmyZZfcnpeXV/Vvl8tFKAMAABDfJAAAAGAdAhoAAIBlCGgAAACWIaABAIBmIyKkpdMl+ITPv0kAAADgSrw+40a1aul2ugyfIKABAIBm4eqwq5wuwWe4xAkAAKwVGRosSerR3vnvx/QlzqABAABr9Y9uo9WTB2ngNQ37Dkt/QUADAABWG9w53OkSfI5LnAAAAJYhoAEAAFiGgAYAAGAZAhoAAIBlCGgAAACWIaABAABYhoAGAABgGQIaAACAZQhoAAAAliGgAQAAWIaABgAAYBkCGgAAgGUIaAAAAJYhoAEAAFiGgAYAAGAZAhoAAIBlCGgAAACWIaABAABYhoAGAABgGQIaAACAZQhoAAAAliGgAQAAWIaA5gPp13V0ugQAAALWsN5XS5KuaXuVw5U0XJDTBQSCh1P66KHkXk6XAQBAQJpyQydlDIxW6+DmE3uaT6XNmLuFSyEt3E6XAQBAQHK5XM0qnElc4gQAALAOAQ0AAMAyBDQAAADLENAAAEDA6tcxzOkSatW83jEHAADQhJ6aeL0KSi84XUYNnEEDAAABK+yqIPXuYN9ZNAIaAACAZQhoAAAAliGgAQAAWIaABgAAYBkCGgAAgGUIaAAAAJYhoAEAAFiGgAYAAGAZAhoAAIBlCGgAAACWIaABAABYhoAGAABgGQIaAACAZbwa0LKzs5WYmKixY8dWjf3ud7/TqFGjlJaWpnvuuUelpaVV21atWqWUlBSNHDlS77zzjjdLAwAAsJZXA9qECRO0Zs2aamNDhgzR1q1btWXLFnXr1k2rVq2SJB09elQ5OTnKycnRmjVrtHjxYnk8Hm+WBwAAYCWvBrT4+HiFh4dXG7v55psVFBQkSYqNjVVhYaEkKTc3V6mpqQoODlaXLl3UtWtX5efne7M8AAAAKwU5ufOXX35Zo0ePliQVFRVp0KBBVds6duyooqKiep/D7XYpIiLUazV+u48W1faReUMnffn1hRr7bUwd3u6hMX7YfyAJ5N4l+g/k/gO5dymw+w/k3iV7+ncsoK1cuVJut1vp6emSJGNMjTkul6ve5/F4jE6fPt/k9X1fRERotX3MG9ZTkmrstzF1eLuHxvhh/4EkkHuX6D+Q+w/k3qXA7j+Qe5e833+HDm0aNM+RgLZp0yZt375dzz33XFUIi46OrrrcKX17Ri0qKsqJ8gAAABzl89ts7NixQ88884xWrlypkJCQqvHk5GTl5OSovLxcJ06c0LFjx3T99df7ujwAAADHefUMWlZWlvbs2aOSkhIlJSVp9uzZWr16tcrLy3XXXXdJkgYNGqTf/va36t27t0aPHq0xY8bI7XZr4cKFcrvd3iwPAADASl4NaMuWLasxNnHixDrnz5w5UzNnzvRmSQAAANbjmwQAAAAsQ0ADAACwDAENAADAMgQ0AAAAyxDQAAAALENAAwAAsAwBDQAAwDIENAAAAMsQ0AAAACxDQAMAALCMV7/qCfV7dXq8Si9UOF0GAACwCAHNYZ3CQ9Qp3OkqAACATbjECQAAYBkCGgAAgGUIaAAAAJYhoAEAAFiGgAYAAGAZAhoAAIBlCGgAAACWIaABAABYhoAGAABgGQIaAACAZQhoAAAAliGgAQAAWIaABgAAYJkgpwvwBwOi2yixWzunywAAAH6CgNYEnvvZYKdLAAAAfoRLnAAAAJYhoAEAAFiGgAYAAGAZAhoAAIBlCGgAAACWIaABAABYhoAGAABgGQIaAACAZQhoAAAAliGgAQAAWIaABgAAYBkCGgAAgGUIaAAAAJYhoAEAAFiGgAYAAGAZAhoAAIBlCGgAAACWIaABAABYhoAGAABgGQIaAACAZQhoAAAAliGgAQAAWIaABgAAYBmXMcY4XQQAAAD+H2fQAAAALENAAwAAsAwBDQAAwDIENAAAAMsQ0AAAACxDQAMAALAMAe17duzYoZEjRyolJUWrV6+usb28vFz333+/UlJSNHHiRJ08edKBKr2nvv5feeUVJSQkKCMjQxkZGdq4caMDVXpHdna2EhMTNXbs2Fq3G2P02GOPKSUlRWlpafrwww99XKH31Nf77t27FRcXV7XuTz75pI8r9J6CggJNnTpVo0ePVmpqqv7yl7/UmOPPa9+Q/v11/cvKypSZman09HSlpqZqxYoVNeb48zG/If378zFfkjwej8aNG6cZM2bU2GbF2hsYY4ypqKgww4cPN8ePHzdlZWUmLS3NHDlypNqc9evXmwULFhhjjNm6dau57777nCjVKxrS/8svv2wWL17sUIXetWfPHnPo0CGTmppa6/bt27ebadOmmcrKSrN//36TmZnp4wq9p77e33vvPfOrX/3Kx1X5RlFRkTl06JAxxpgzZ86YESNG1Ph/789r35D+/XX9KysrzdmzZ40xxpSXl5vMzEyzf//+anP8+ZjfkP79+ZhvjDFr1641WVlZtf7/tmHtOYP2nfz8fHXt2lVdunRRcHCwUlNTlZubW21OXl6exo8fL0kaOXKkdu3aJeMn9/ltSP/+LD4+XuHh4XVuz83N1bhx4+RyuRQbG6vS0lKdOnXKhxV6T329+7OoqCgNGDBAkhQWFqYePXqoqKio2hx/XvuG9O+vXC6XWrduLUmqqKhQRUWFXC5XtTn+fMxvSP/+rLCwUNu3b1dmZmat221YewLad4qKihQdHV31uGPHjjUOVEVFRbrmmmskSUFBQWrTpo1KSkp8Wqe3NKR/SXrjjTeUlpamOXPmqKCgwJclOuqHr090dHTA/CKTpAMHDig9PV3Tp0/XkSNHnC7HK06ePKmPP/5YgwYNqjYeKGtfV/+S/66/x+NRRkaGbrrpJt100021rr2/HvOl+vuX/PeYv2TJEs2dO1ctWtQeg2xYewLad2pLxj/8a6Ihc5qrhvQ2bNgw5eXlacuWLUpMTNS8efN8VZ7j/Hnt6zNgwADl5eXptdde09SpU3XPPfc4XVKTO3funObMmaOHH35YYWFh1bYFwtpfqn9/Xn+3263Nmzfr7bffVn5+vg4fPlxtu7+vfX39++sx/6233lJkZKSuu+66OufYsPYEtO9ER0ersLCw6nFRUZGioqJqzPnPXxAVFRU6c+aMIiIifFqntzSk/3bt2ik4OFiSNGnSJL96s3R9fvj6FBYW1nh9/FVYWFjVpZChQ4eqoqJCxcXFDlfVdC5evKg5c+YoLS1NI0aMqLHd39e+vv79ff0lqW3btrrxxhv1zjvvVBv352P+99XVv78e8z/44APl5eUpOTlZWVlZeu+99/TQQw9Vm2PD2hPQvjNw4EAdO3ZMJ06cUHl5uXJycpScnFxtTnJysjZt2iRJ2rZtmxISEvzmr6mG9P/9993k5eWpZ8+evi7TMcnJyXr11VdljNGBAwfUpk0bv/olfSn/+te/qv6azM/PV2Vlpdq1a+dwVU3DGKPf/OY36tGjh+66665a5/jz2jekf39d/+LiYpWWlkqSLly4oJ07d6pHjx7V5vjzMb8h/fvrMf/BBx/Ujh07lJeXp2XLlikhIUFLly6tNseGtQ/y6d4sFhQUpIULF2r69OnyeDy69dZb1bt3b/3pT3/Sddddp+HDhyszM1Nz585VSkqKwsPDtXz5cqfLbjIN6X/dunXKy8uT2+1WeHi4Hn/8cafLbjJZWVnas2ePSkpKlJSUpNmzZ6uiokKSNGXKFA0dOlRvv/22UlJSFBISoiVLljhccdOpr/dt27bphRdekNvtVqtWrbRs2TK/+SW1b98+bd68WX369FFGRoakb1+PL7/8UpL/r31D+vfX9T916pTmz58vj8cjY4xGjRqlYcOGBcwxvyH9+/Mxvza2rb3L+MtHUgAAAPwElzgBAAAsQ0ADAACwDAENAADAMgQ0AAAAy/ApTgAAgHpkZ2dr+/btat++vbZu3XrJuUuWLNHu3bslfXsbk6+++krvv//+Ze2PT3ECAADUY+/evQoNDdW8efPqDWjft27dOn300UeXfZsSLnECaNaSk5MdubP91KlT9fe//73O7U8//bQPqwHgbfHx8QoPD682dvz4cU2bNk0TJkzQ7bffrk8//bTGz+Xk5Gjs2LGXvT8CGgB4wapVq5wuAYCXLViwQAsWLNArr7yiefPmafHixdW2f/HFFzp58qQSEhIu+7l5DxqAZmPz5s1at26dLl68qEGDBmnRokXVts+aNUuFhYUqKyvTHXfcocmTJ0uSBg8erMmTJ2v37t1q27atli9frsjISD3//PPasGGD3G63evXqpeXLl+v8+fN69NFHdfjwYXk8Ht1777265ZZbdOHCBWVnZ+vo0aPq2bOnLly4UGedS5cu1YULF5SRkaFevXrpgQce0PTp0xUXF6eDBw8qJiZGt956q1asWKHi4mItXbpU119/vVdfOwBN69y5c9q/f7/uu+++qrHy8vJqc3JycjRy5Ei53e7L34EBgGbg6NGjZsaMGaa8vNwYY8yiRYvMpk2bzLBhw8xXX31ljDGmpKTEGGPMN998Y1JTU01xcbExxpg+ffqYzZs3G2OM+fOf/2wWL15sjDFmyJAhpqyszBhjzNdff22MMeYPf/iDefXVV6vGRowYYc6dO2fWrl1r5s+fb4wx5uOPPzb9+vUz+fn5ddYbGxtb9e8TJ06Yfv36mX/84x/G4/GY8ePHm/nz55vKykrz5ptvmpkzZzbNiwTAq06cOGFSU1ONMcacOXPGDBky5JLzMzIyzL59+65oX5xBA9As7Nq1S4cOHVJmZqakbz8Z1b59+2pz1q1bpzfffFOSVFBQoH/+859q166dWrRooTFjxkiSMjIydO+990qSYmJi9NBDD2n48OG65ZZbJEnvvvuu8vLytHbtWklSWVmZCgoKtHfvXk2dOlWS1LdvX8XExFxW/Z07d676mV69eikxMVEul0sxMTH64osvruQlAeCgsLAwde7cWa+//rpGjx4tY4w++eQT9e3bV5L02WefqbS0VIMHD76i5yegAWgWjDEaP368HnzwwWrjmzZtkiTt3r1bO3fu1IsvvqiQkBBNnTpVZWVltT7Xf77se/Xq1dq7d6/y8vL01FNPKScnR5K0YsUK9ejRo86fuxLBwcFV/27RokXVY5fLJY/Hc8XPC8A3srKytGfPHpWUlCgpKUmzZ8/W73//ez3yyCNauXKlKioqNGbMmKqAlpOTozFjxlzxcYOABqBZSExM1KxZs3TnnXeqffv2On36tM6dO1e1/cyZMwoPD1dISIg+/fRTHThwoGpbZWWltm3bptTUVG3ZskVxcXGqrKxUQUGBEhISFBcXp61bt+r8+fO6+eabtX79ei1YsEAul0sfffSR+vfvr/j4eG3ZskUJCQk6fPiwPvnkk0vWGxQUpIsXL6ply5Zee00A+M6yZctqHX/22WdrHZ89e3aj9kdAA9As9OrVS/fff7/uvvtuVVZWqmXLllq4cGHV9qSkJG3YsEFpaWnq3r27YmNjq7aFhobqyJEjmjBhgsLCwvTHP/5RHo9Hc+fO1dmzZ2WM0Z133qm2bdtq1qxZWrJkidLT02WMUadOnbRq1SpNmTJF2dnZSktLU79+/ep9U/+kSZOUnp6u/v3764EHHvDa6wLAP3GjWgB+b/Dgwdq/f7/TZQBAg3EfNAAAAMtwBg0AGmHixIk17n30xBNPXPanPAHg+whoAAAAluESJwAAgGUIaAAAAJYhoAEAAFiGgAYAAGAZAhoAAIBl/g9DmEwiUwe0xgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting EVBOV_MAX, one of the 12 values, where outliers are having a huge effect\n",
    "sns.lineplot(y = \"EVBOV_MAX\", x = \"elapsed_tm\", data = t_data)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Butterflow Low pass filter attempt - 01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def butter_lowpass(cutoff, fs, order=5):\n",
    "    \"\"\"\n",
    "    butterworth low pass filter logic\n",
    "    nyq - nyquest frequency\n",
    "    \"\"\"\n",
    "    nyq = 0.5 * fs\n",
    "    normal_cutoff = cutoff / nyq\n",
    "    b, a = butter(order, normal_cutoff, btype='low', analog = False)\n",
    "    return b, a\n",
    "\n",
    "\n",
    "def butter_lowpass_filter(data, cutoff, fs, order=5):\n",
    "    \"\"\"\n",
    "    calling the function butter_lowpass\n",
    "    \"\"\"\n",
    "    b, a = butter_lowpass(cutoff, fs, order=order)\n",
    "    y = lfilter(b, a, data)\n",
    "    return y\n",
    "\n",
    "\n",
    "# Parameters of Butterworth filter\n",
    "order = 1       #order of butterworth filter\n",
    "fs = 10         # sample rate, Hz\n",
    "cutoff = 0.05   # desired cutoff frequency of the filter, Hz\n",
    "\n",
    "# Get the filter coefficients so we can check its frequency response.\n",
    "b, a = butter_lowpass(cutoff, fs, order)\n",
    "\n",
    "# Plot the frequency response.\n",
    "w, h = freqz(b, a, worN=t_data.elapsed_tm.max())\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.plot(0.5*fs*w/np.pi, np.abs(h), 'b')\n",
    "plt.plot(cutoff, 0.5*np.sqrt(2), 'ko')\n",
    "plt.axvline(cutoff, color='k')\n",
    "plt.xlim(0, 0.5*fs)\n",
    "plt.title(\"Lowpass Filter Frequency Response\")\n",
    "plt.xlabel('Frequency [Hz]')\n",
    "plt.grid()\n",
    "\n",
    "\n",
    "# Demonstrate the use of the filter.\n",
    "# First make some data to be filtered.\n",
    "T = t_data.elapsed_tm.max()            # seconds\n",
    "n = int(T * fs)                        # total number of samples\n",
    "t = np.linspace(0, T, len(t_data), endpoint=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = t_data[\"EVBOV_MAX\"].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = butter_lowpass_filter(d, cutoff, fs, order)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(2, 1, 2)\n",
    "plt.plot(t[4750:4850], d[4750:4850], 'b-', label='data')\n",
    "plt.plot(t[4750:4850], y[4750:4850], 'g-', linewidth=2, label='filtered data')\n",
    "plt.xlabel('Time [sec]')\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "\n",
    "plt.subplots_adjust(hspace=0.35)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "#t_data[t_data[\"EVBOV_MAX\"] < 170]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(\"/home/CWSHPMU2316\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data = pd.read_csv(\"input.csv\", header = None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18.103689</td>\n",
       "      <td>77.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18.203931</td>\n",
       "      <td>77.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18.303728</td>\n",
       "      <td>77.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>18.404227</td>\n",
       "      <td>77.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18.504190</td>\n",
       "      <td>78.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           0     1\n",
       "0  18.103689  77.2\n",
       "1  18.203931  77.2\n",
       "2  18.303728  77.2\n",
       "3  18.404227  77.2\n",
       "4  18.504190  78.7"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data.columns = [\"time\", \"EVSMA_CAN\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23712"
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(new_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## RC Filter Logic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rc_logic(arr):\n",
    "    \"\"\"\n",
    "    This function implements the RC Filter\n",
    "    \"\"\"\n",
    "    RC = 30\n",
    "    T = 0.1\n",
    "    alpha = (2*RC)/T \n",
    "    \n",
    "    rc_list = []\n",
    "    \n",
    "    x0 = 0      # x(n-1) value\n",
    "    y0 = 0      # y(n-1) value\n",
    "    for i in range(0, len(arr)):\n",
    "        xi = arr[i]\n",
    "        yi = ((xi + x0) - ((1-alpha)*y0))/(1+alpha)\n",
    "        rc_list.append(yi)\n",
    "        x0 = xi\n",
    "        y0 = yi\n",
    "    \n",
    "    return rc_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [],
   "source": [
    "# passing an numpy array of EVBOV_MAX\n",
    "#arr = rc_logic(data[\"EVSMA_CAN\"].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [],
   "source": [
    "yhat = rc_logic(data[\"EVSMA_MAX\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(data[\"EVSMA_MAX\"][12000:20000].values, label = \"TCU Value\")\n",
    "#plt.plot(yhat[5000:12000], label = \"RC Filtered Value\")\n",
    "plt.plot(new_data[\"EVSMA_CAN\"][12000:20000].values, label = \"CAN data\")\n",
    "plt.plot(series[\"EVSMA_EWMA\"][12000:20000].values, label = \"EXP Value\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(data[\"EVSMA_MAX\"].values)\n",
    "plt.plot(yhat)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Savitzky Golay Filter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "polynomial_order = 2 # order of polynomial\n",
    "window = 61          # must be an odd integer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "smooth_signal = savgol_filter(data[\"EVSMA_MAX\"].values, window, polynomial_order)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(data[\"EVSMA_MAX\"][10000:20000].values)\n",
    "plt.plot(smooth_signal[10000:20000])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exponential Moving Averages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [],
   "source": [
    "name = \"EVSMA\"\n",
    "series = data[\"EVSMA_MAX\"].to_frame()\n",
    "span = 600\n",
    "alpha = 2/(1 + span)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>EVSMA_MAX</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>43207</th>\n",
       "      <td>88.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23464</th>\n",
       "      <td>93.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18312</th>\n",
       "      <td>59.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54185</th>\n",
       "      <td>76.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22212</th>\n",
       "      <td>93.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       EVSMA_MAX\n",
       "43207       88.0\n",
       "23464       93.0\n",
       "18312       59.8\n",
       "54185       76.9\n",
       "22212       93.1"
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [],
   "source": [
    "series[name + '_EWMA'] = np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>EVSMA_MAX</th>\n",
       "      <th>EVSMA_EWMA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>78.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>78.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>78.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>78.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>78.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   EVSMA_MAX  EVSMA_EWMA\n",
       "0       78.4         NaN\n",
       "1       78.4         NaN\n",
       "2       78.4         NaN\n",
       "3       78.4         NaN\n",
       "4       78.4         NaN"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [],
   "source": [
    "series.loc[0, name + '_EWMA'] = series[\"EVSMA_MAX\"].iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>EVSMA_MAX</th>\n",
       "      <th>EVSMA_EWMA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>78.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>78.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>78.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>78.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   EVSMA_MAX  EVSMA_EWMA\n",
       "0       78.4        78.4\n",
       "1       78.4         NaN\n",
       "2       78.4         NaN\n",
       "3       78.4         NaN\n",
       "4       78.4         NaN"
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [],
   "source": [
    "#series[name+'_EWMA_adjusted'] = np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [],
   "source": [
    "#series.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(1, len(series)):\n",
    "    temp = (series[\"EVSMA_MAX\"][i]*alpha) + (series[\"EVSMA_EWMA\"][i-1]*(1-alpha))\n",
    "    series[\"EVSMA_EWMA\"][i] = temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>EVSMA_MAX</th>\n",
       "      <th>EVSMA_EWMA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>78.4</td>\n",
       "      <td>78.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   EVSMA_MAX  EVSMA_EWMA\n",
       "0       78.4        78.4\n",
       "1       78.4        78.4\n",
       "2       78.4        78.4\n",
       "3       78.4        78.4\n",
       "4       78.4        78.4"
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(series[\"EVSMA_MAX\"], label = \"Actual\")\n",
    "plt.plot(series[\"EVSMA_EWMA\"], label = \"Exp MA\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(series[\"EVSMA_MAX\"][10000:20000], label = \"Actual\")\n",
    "plt.plot(series[\"EVSMA_EWMA\"][10000:20000], label = \"Exp MA\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
